uczenie-maszynowe/wyk/06_Problem_nadmiernego_dopasowania.ipynb
2023-04-13 09:46:29 +02:00

1833 lines
581 KiB
Plaintext
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Uczenie maszynowe\n",
"# 6. Problem nadmiernego dopasowania"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 6.1. Regresja wielomianowa"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Wprowadzenie: wybór cech"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Niech naszym zadaniem będzie przewidzieć cenę działki o kształcie prostokąta.\n",
"\n",
"Jakie cechy wybrać?"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Możemy wybrać dwie cechy:"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
" * $x_1$ szerokość działki, $x_2$ długość działki:\n",
"$$ h_{\\theta}(\\vec{x}) = \\theta_0 + \\theta_1 x_1 + \\theta_2 x_2 $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"...albo jedną:"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
" * $x_1$ powierzchnia działki:\n",
"$$ h_{\\theta}(\\vec{x}) = \\theta_0 + \\theta_1 x_1 $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Można też zauważyć, że cecha „powierzchnia działki” powstaje przez pomnożenie dwóch innych cech: długości działki i jej szerokości."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"**Wniosek:** możemy tworzyć nowe cechy na podstawie innych poprzez wykonywanie na nich różnych operacji matematycznych."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Regresja wielomianowa"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"W regresji wielomianowej będziemy korzystać z cech, które utworzymy jako potęgi cech wyjściowych."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"# Przydatne importy\n",
"\n",
"import ipywidgets as widgets\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"# Przydatne funkcje\n",
"\n",
"\n",
"def cost(theta, X, y):\n",
" \"\"\"Wersja macierzowa funkcji kosztu\"\"\"\n",
" m = len(y)\n",
" J = 1.0 / (2.0 * m) * ((X * theta - y).T * (X * theta - y))\n",
" return J.item()\n",
"\n",
"\n",
"def gradient(theta, X, y):\n",
" \"\"\"Wersja macierzowa gradientu funkcji kosztu\"\"\"\n",
" return 1.0 / len(y) * (X.T * (X * theta - y))\n",
"\n",
"\n",
"def gradient_descent(fJ, fdJ, theta, X, y, alpha=0.1, eps=10**-5):\n",
" \"\"\"Algorytm gradientu prostego (wersja macierzowa)\"\"\"\n",
" current_cost = fJ(theta, X, y)\n",
" logs = [[current_cost, theta]]\n",
" while True:\n",
" theta = theta - alpha * fdJ(theta, X, y)\n",
" current_cost, prev_cost = fJ(theta, X, y), current_cost\n",
" if abs(prev_cost - current_cost) > 10**15:\n",
" print(\"Algorithm does not converge!\")\n",
" break\n",
" if abs(prev_cost - current_cost) <= eps:\n",
" break\n",
" logs.append([current_cost, theta])\n",
" return theta, logs\n",
"\n",
"\n",
"def plot_data(X, y, xlabel, ylabel):\n",
" \"\"\"Wykres danych (wersja macierzowa)\"\"\"\n",
" fig = plt.figure(figsize=(16 * 0.6, 9 * 0.6))\n",
" ax = fig.add_subplot(111)\n",
" fig.subplots_adjust(left=0.1, right=0.9, bottom=0.1, top=0.9)\n",
" ax.scatter([X[:, 1]], [y], c=\"r\", s=50, label=\"Dane\")\n",
"\n",
" ax.set_xlabel(xlabel)\n",
" ax.set_ylabel(ylabel)\n",
" ax.margins(0.05, 0.05)\n",
" plt.ylim(y.min() - 1, y.max() + 1)\n",
" plt.xlim(np.min(X[:, 1]) - 1, np.max(X[:, 1]) + 1)\n",
" return fig\n",
"\n",
"\n",
"def plot_fun(fig, fun, X):\n",
" \"\"\"Wykres funkcji `fun`\"\"\"\n",
" ax = fig.axes[0]\n",
" x0 = np.min(X[:, 1]) - 1.0\n",
" x1 = np.max(X[:, 1]) + 1.0\n",
" Arg = np.arange(x0, x1, 0.1)\n",
" Val = fun(Arg)\n",
" return ax.plot(Arg, Val, linewidth=\"2\")\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"# Wczytanie danych (mieszkania) przy pomocy biblioteki pandas\n",
"\n",
"alldata = pandas.read_csv(\n",
" \"data_flats.tsv\", header=0, sep=\"\\t\", usecols=[\"price\", \"rooms\", \"sqrMetres\"]\n",
")\n",
"data = np.matrix(alldata[[\"sqrMetres\", \"price\"]])\n",
"\n",
"m, n_plus_1 = data.shape\n",
"n = n_plus_1 - 1\n",
"Xn = data[:, 0:n]\n",
"Xn /= np.amax(Xn, axis=0)\n",
"Xn2 = np.power(Xn, 2)\n",
"Xn2 /= np.amax(Xn2, axis=0)\n",
"Xn3 = np.power(Xn, 3)\n",
"Xn3 /= np.amax(Xn3, axis=0)\n",
"\n",
"X = np.matrix(np.concatenate((np.ones((m, 1)), Xn), axis=1)).reshape(m, n + 1)\n",
"X2 = np.matrix(np.concatenate((np.ones((m, 1)), Xn, Xn2), axis=1)).reshape(m, 2 * n + 1)\n",
"X3 = np.matrix(np.concatenate((np.ones((m, 1)), Xn, Xn2, Xn3), axis=1)).reshape(\n",
" m, 3 * n + 1\n",
")\n",
"y = np.matrix(data[:, -1]).reshape(m, 1)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Postać ogólna regresji wielomianowej:\n",
"\n",
"$$ h_{\\theta}(x) = \\sum_{i=0}^{n} \\theta_i x^i $$"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [],
"source": [
"# Funkcja regresji wielomianowej\n",
"\n",
"\n",
"def h_poly(Theta, x):\n",
" \"\"\"Funkcja wielomianowa\"\"\"\n",
" return sum(theta * np.power(x, i) for i, theta in enumerate(Theta.tolist()))\n",
"\n",
"\n",
"def polynomial_regression(theta):\n",
" \"\"\"Funkcja regresji wielomianowej\"\"\"\n",
" return lambda x: h_poly(theta, x)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Najprostszym przypadkiem regresji wielomianowej jest funkcja kwadratowa:"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Funkcja kwadratowa:\n",
"\n",
"$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 $$"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f4283c91b10>]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data(X2, y, xlabel=\"x\", ylabel=\"y\")\n",
"theta_start = np.matrix([0, 0, 0]).reshape(3, 1)\n",
"theta, logs = gradient_descent(cost, gradient, theta_start, X2, y)\n",
"plot_fun(fig, polynomial_regression(theta), X)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Innym szczególnym przypadkiem regresji wielomianowej jest funkjca sześcienna:"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Funkcja sześcienna:\n",
"\n",
"$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 + \\theta_3 x^3 $$"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 397519.38046962]\n",
" [-841341.14146733]\n",
" [2253713.97125102]\n",
" [-244009.07081946]]\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data(X3, y, xlabel=\"x\", ylabel=\"y\")\n",
"theta_start = np.matrix([0, 0, 0, 0]).reshape(4, 1)\n",
"theta, _ = gradient_descent(cost, gradient, theta_start, X3, y)\n",
"plot_fun(fig, polynomial_regression(theta), X)\n",
"\n",
"print(theta)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Regresję wielomianową można potraktować jako szczególny przypadek regresji liniowej wielu zmiennych:\n",
"\n",
"$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 x^2 + \\theta_3 x^3 $$\n",
"$$ x_1 = x, \\quad x_2 = x^2, \\quad x_3 = x^3, \\quad \\vec{x} = \\left[ \\begin{array}{ccc} x_0 \\\\ x_1 \\\\ x_2 \\end{array} \\right] $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"(W tym przypadku za kolejne cechy przyjmujemy kolejne potęgi zmiennej $x$)."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Uwaga praktyczna: przyda się normalizacja cech, szczególnie skalowanie!"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Do tworzenia cech „pochodnych” możemy używać nie tylko potęgowania, ale też innych operacji matematycznych, np.:\n",
"\n",
"$$ h_{\\theta}(x) = \\theta_0 + \\theta_1 x + \\theta_2 \\sqrt{x} $$\n",
"$$ x_1 = x, \\quad x_2 = \\sqrt{x}, \\quad \\vec{x} = \\left[ \\begin{array}{ccc} x_0 \\\\ x_1 \\end{array} \\right] $$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Jakie zatem cechy wybrać? Najlepiej dopasować je do konkretnego problemu."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Wielomianowa regresja logistyczna\n",
"\n",
"Podobne modyfikacje cech możemy również stosować dla regresji logistycznej."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def powerme(x1, x2, n):\n",
" \"\"\"Funkcja, która generuje n potęg dla zmiennych x1 i x2 oraz ich iloczynów\"\"\"\n",
" X = []\n",
" for m in range(n + 1):\n",
" for i in range(m + 1):\n",
" X.append(np.multiply(np.power(x1, i), np.power(x2, (m - i))))\n",
" return np.hstack(X)\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [
{
"data": {
"text/plain": [
"matrix([[ 1. , 0.36596696, -0.11214686],\n",
" [ 0. , 0.4945305 , 0.47110656],\n",
" [ 0. , 0.70290604, -0.92257983],\n",
" [ 0. , 0.46658862, -0.62269739],\n",
" [ 0. , 0.87939462, -0.11408015],\n",
" [ 0. , -0.331185 , 0.84447667],\n",
" [ 0. , -0.54351701, 0.8851383 ],\n",
" [ 0. , 0.91979241, 0.41607012],\n",
" [ 0. , 0.28011742, 0.61431157],\n",
" [ 0. , 0.94754363, -0.78307311]])"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Wczytanie danych\n",
"import pandas\n",
"import numpy as np\n",
"\n",
"alldata = pandas.read_csv(\"polynomial_logistic.tsv\", sep=\"\\t\")\n",
"data = np.matrix(alldata)\n",
"\n",
"m, n_plus_1 = data.shape\n",
"n = n_plus_1 - 1\n",
"Xn = data[:, 1:]\n",
"\n",
"Xpl = powerme(data[:, 1], data[:, 2], n)\n",
"Ypl = np.matrix(data[:, 0]).reshape(m, 1)\n",
"\n",
"data[:10]\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def plot_data_for_classification(X, Y, xlabel, ylabel):\n",
" \"\"\"Wykres danych (wersja macierzowa)\"\"\"\n",
" fig = plt.figure(figsize=(16 * 0.6, 9 * 0.6))\n",
" ax = fig.add_subplot(111)\n",
" fig.subplots_adjust(left=0.1, right=0.9, bottom=0.1, top=0.9)\n",
" X = X.tolist()\n",
" Y = Y.tolist()\n",
" X1n = [x[1] for x, y in zip(X, Y) if y[0] == 0]\n",
" X1p = [x[1] for x, y in zip(X, Y) if y[0] == 1]\n",
" X2n = [x[2] for x, y in zip(X, Y) if y[0] == 0]\n",
" X2p = [x[2] for x, y in zip(X, Y) if y[0] == 1]\n",
" ax.scatter(X1n, X2n, c=\"r\", marker=\"x\", s=50, label=\"Dane\")\n",
" ax.scatter(X1p, X2p, c=\"g\", marker=\"o\", s=50, label=\"Dane\")\n",
"\n",
" ax.set_xlabel(xlabel)\n",
" ax.set_ylabel(ylabel)\n",
" ax.margins(0.05, 0.05)\n",
" return fig\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Przyjmijmy, że mamy następujące dane i chcemy przeprowadzić klasyfikację dwuklasową dla następujących klas:\n",
" * czerwone krzyżyki\n",
" * zielone kółka"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data_for_classification(Xpl, Ypl, xlabel=r\"$x_1$\", ylabel=r\"$x_2$\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Propozycja hipotezy:\n",
"\n",
"$$ h_\\theta(x) = g(\\theta^T x) = g(\\theta_0 + \\theta_1 x_1 + \\theta_2 x_2 + \\theta_3 x_3 + \\theta_4 x_4 + \\theta_5 x_5) \\; , $$\n",
"\n",
"gdzie $g$ funkcja logistyczna, $x_3 = x_1^2$, $x_4 = x_2^2$, $x_5 = x_1 x_2$."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def safeSigmoid(x, eps=0):\n",
" \"\"\"Funkcja sigmoidalna zmodyfikowana w taki sposób,\n",
" żeby wartości zawsz były odległe od asymptot o co najmniej eps\n",
" \"\"\"\n",
" y = 1.0 / (1.0 + np.exp(-x))\n",
" if eps > 0:\n",
" y[y < eps] = eps\n",
" y[y > 1 - eps] = 1 - eps\n",
" return y\n",
"\n",
"\n",
"def h(theta, X, eps=0.0):\n",
" \"\"\"Funkcja hipotezy\"\"\"\n",
" return safeSigmoid(X * theta, eps)\n",
"\n",
"\n",
"def J(h, theta, X, y, lamb=0):\n",
" \"\"\"Funkcja kosztu\"\"\"\n",
" m = len(y)\n",
" f = h(theta, X, eps=10**-7)\n",
" j = (\n",
" -np.sum(np.multiply(y, np.log(f)) + np.multiply(1 - y, np.log(1 - f)), axis=0)\n",
" / m\n",
" )\n",
" if lamb > 0:\n",
" j += lamb / (2 * m) * np.sum(np.power(theta[1:], 2))\n",
" return j\n",
"\n",
"\n",
"def dJ(h, theta, X, y, lamb=0):\n",
" \"\"\"Pochodna funkcji kosztu\"\"\"\n",
" g = 1.0 / y.shape[0] * (X.T * (h(theta, X) - y))\n",
" if lamb > 0:\n",
" g[1:] += lamb / float(y.shape[0]) * theta[1:]\n",
" return g\n",
"\n",
"\n",
"def classifyBi(theta, X):\n",
" \"\"\"Funkcja decyzji\"\"\"\n",
" prob = h(theta, X)\n",
" return prob\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def GD(h, fJ, fdJ, theta, X, y, alpha=0.01, eps=10**-3, maxSteps=10000):\n",
" \"\"\"Metoda gradientu prostego dla regresji logistycznej\"\"\"\n",
" errorCurr = fJ(h, theta, X, y)\n",
" errors = [[errorCurr, theta]]\n",
" while True:\n",
" # oblicz nowe theta\n",
" theta = theta - alpha * fdJ(h, theta, X, y)\n",
" # raportuj poziom błędu\n",
" errorCurr, errorPrev = fJ(h, theta, X, y), errorCurr\n",
" # kryteria stopu\n",
" if abs(errorPrev - errorCurr) <= eps:\n",
" break\n",
" if len(errors) > maxSteps:\n",
" break\n",
" errors.append([errorCurr, theta])\n",
" return theta, errors\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"theta = [[ 1.59558981]\n",
" [ 0.12602307]\n",
" [ 0.65718518]\n",
" [-5.26367581]\n",
" [ 1.96832544]\n",
" [-6.97946065]]\n"
]
}
],
"source": [
"# Uruchomienie metody gradientu prostego dla regresji logistycznej\n",
"theta_start = np.matrix(np.zeros(Xpl.shape[1])).reshape(Xpl.shape[1], 1)\n",
"theta, errors = GD(\n",
" h, J, dJ, theta_start, Xpl, Ypl, alpha=0.1, eps=10**-7, maxSteps=10000\n",
")\n",
"print(r\"theta = {}\".format(theta))\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def plot_decision_boundary(fig, theta, X):\n",
" \"\"\"Wykres granicy klas\"\"\"\n",
" ax = fig.axes[0]\n",
" xx, yy = np.meshgrid(np.arange(-1.0, 1.0, 0.02), np.arange(-1.0, 1.0, 0.02))\n",
" l = len(xx.ravel())\n",
" C = powerme(xx.reshape(l, 1), yy.reshape(l, 1), n)\n",
" z = classifyBi(theta, C).reshape(int(np.sqrt(l)), int(np.sqrt(l)))\n",
"\n",
" plt.contour(xx, yy, z, levels=[0.5], lw=3)\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_3088/1169766636.py:9: UserWarning: The following kwargs were not used by contour: 'lw'\n",
" plt.contour(xx, yy, z, levels=[0.5], lw=3)\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data_for_classification(Xpl, Ypl, xlabel=r\"$x_1$\", ylabel=r\"$x_2$\")\n",
"plot_decision_boundary(fig, theta, Xpl)\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"# Wczytanie danych\n",
"\n",
"alldata = pandas.read_csv(\"polynomial_logistic.tsv\", sep=\"\\t\")\n",
"data = np.matrix(alldata)\n",
"\n",
"m, n_plus_1 = data.shape\n",
"Xn = data[:, 1:]\n",
"\n",
"n = 10\n",
"Xpl = powerme(data[:, 1], data[:, 2], n)\n",
"Ypl = np.matrix(data[:, 0]).reshape(m, 1)\n",
"\n",
"theta_start = np.matrix(np.zeros(Xpl.shape[1])).reshape(Xpl.shape[1], 1)\n",
"theta, errors = GD(\n",
" h, J, dJ, theta_start, Xpl, Ypl, alpha=0.1, eps=10**-7, maxSteps=10000\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_3088/1169766636.py:9: UserWarning: The following kwargs were not used by contour: 'lw'\n",
" plt.contour(xx, yy, z, levels=[0.5], lw=3)\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Przykład dla większej liczby cech\n",
"fig = plot_data_for_classification(Xpl, Ypl, xlabel=r\"$x_1$\", ylabel=r\"$x_2$\")\n",
"plot_decision_boundary(fig, theta, Xpl)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 6.2. Problem nadmiernego dopasowania"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Obciążenie a wariancja"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"# Dane do prostego przykładu\n",
"\n",
"data = np.matrix(\n",
" [\n",
" [0.0, 0.0],\n",
" [0.5, 1.8],\n",
" [1.0, 4.8],\n",
" [1.6, 7.2],\n",
" [2.6, 8.8],\n",
" [3.0, 9.0],\n",
" ]\n",
")\n",
"\n",
"m, n_plus_1 = data.shape\n",
"n = n_plus_1 - 1\n",
"Xn1 = data[:, 0:n]\n",
"Xn1 /= np.amax(Xn1, axis=0)\n",
"Xn2 = np.power(Xn1, 2)\n",
"Xn2 /= np.amax(Xn2, axis=0)\n",
"Xn3 = np.power(Xn1, 3)\n",
"Xn3 /= np.amax(Xn3, axis=0)\n",
"Xn4 = np.power(Xn1, 4)\n",
"Xn4 /= np.amax(Xn4, axis=0)\n",
"Xn5 = np.power(Xn1, 5)\n",
"Xn5 /= np.amax(Xn5, axis=0)\n",
"\n",
"X1 = np.matrix(np.concatenate((np.ones((m, 1)), Xn1), axis=1)).reshape(m, n + 1)\n",
"X2 = np.matrix(np.concatenate((np.ones((m, 1)), Xn1, Xn2), axis=1)).reshape(\n",
" m, 2 * n + 1\n",
")\n",
"X5 = np.matrix(\n",
" np.concatenate((np.ones((m, 1)), Xn1, Xn2, Xn3, Xn4, Xn5), axis=1)\n",
").reshape(m, 5 * n + 1)\n",
"y = np.matrix(data[:, -1]).reshape(m, 1)\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA00AAAH0CAYAAADhWca4AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8o6BhiAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAlLklEQVR4nO3df3CU9Z3A8U9+lJCKG4oKgTEq/jhsxYqtymAUdeTKtZ4DMuNVz3Oo1ztPGk+Bnq3ejDrW01SvA07vBHrenDpetdpe0dOrOohVCSL+QkutR9VyylkTrdasYhol+9wfW9KLkC+/kuwmeb1mdjL77HfTT/p0Sd59nme3IsuyLAAAANiuylIPAAAAUM5EEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQEJJo+mxxx6L008/PSZMmBAVFRVx991393g8y7K44oorYvz48VFbWxszZsyIl156qTTDAgAAw1JJo2nz5s1x1FFHxY033rjdx6+//vr47ne/G8uWLYu1a9fGXnvtFTNnzozf/e53AzwpAAAwXFVkWZaVeoiIiIqKili+fHnMnj07IopHmSZMmBBf//rX4+/+7u8iIqK9vT3GjRsXt9xyS5x11lklnBYAABguqks9QG82btwYra2tMWPGjO5tdXV1MXXq1FizZk2v0dTZ2RmdnZ3d9wuFQrzzzjuxzz77REVFRb/PDQAAlE6WZfHee+/FhAkTorKyb06sK9toam1tjYiIcePG9dg+bty47se2p7m5Oa666qp+nQ0AAChvmzZtiv33379PvlfZRtPuuuyyy2LhwoXd99vb2+OAAw6ITZs2RS6XK+FkAABAf8vn89HQ0BB77713n33Pso2m+vr6iIhoa2uL8ePHd29va2uLKVOm9Pq8mpqaqKmp2WZ7LpcTTQAAMEz05aU5Zfs5TRMnToz6+vpYuXJl97Z8Ph9r166NadOmlXAyAABgOCnpkab3338/Xn755e77GzdujOeeey7GjBkTBxxwQMyfPz/+4R/+IQ477LCYOHFiXH755TFhwoTud9gDAADobyWNpqeffjpOOeWU7vtbr0WaO3du3HLLLfGNb3wjNm/eHOeff368++67ccIJJ8QDDzwQI0eOLNXIAADAMFM2n9PUX/L5fNTV1UV7e7trmgAAYIjrj7//y/aaJgAAgHIgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAw9HR0RLS1Fb8C7CHRBAAMHS0tEXPmRIwaFVFfX/w6Z07E6tWlngwYxEQTADA0LF0aMX16xL33RhQKxW2FQvH+iSdGLFtW2vmAQUs0AQCDX0tLRFNTRJZFbNnS87EtW4rbv/Y1R5yA3SKaAIDBb9GiiKqq9JqqqojFiwdmHmBIEU0AwODW0RFxzz3bHmH6uC1bIpYv9+YQwC4TTQDA4JbP/+Eaph0pFIrrAXaBaAIABrdcLqJyJ/+kqawsrgfYBaIJAOg7pfh8pNraiFmzIqqr0+uqqyPOOKO4HmAXiCYAYM+V+vORFi6M6OpKr+nqiliwYGDmAYYU0QQA7Jly+HykE06IWLIkoqJi2yNO1dXF7UuWRDQ29v8swJAjmgCA3VdOn490wQURq1YVT9Xbeo1TZWXx/qpVxccBdsMOTv4FAEjY+vlIqbf73vr5SANxlKexsXjr6Ci+S14u5xomYI+JJgBg92z9fKQdvd33//98pIEKmNpasQT0GafnAQC7x+cjAcOEaAIAdo/PRwKGCdEEAOwen48EDBOiCQDYfT4fCRgGRBMAsPt8PhIwDIgmAGDP+HwkYIjzluMAwJ7z+UjAECaaAIC+4/ORgCHI6XkAAAAJogkAACBBNAEAACSIJgAAgATRBAAAkCCaAAAAEkQTAABAgmgCAABIEE0AAAAJogkAACBBNAEAACSIJgAAgATRBAAAkCCaAAAAEkQTAABAgmgCAABIEE0AAAAJogkAACBBNAEAACSIJgAAgISyjqaurq64/PLLY+LEiVFbWxuHHHJIXH311ZFlWalHAwAAhonqUg+Qct1118XSpUvj1ltvjSOOOCKefvrpOO+886Kuri4uuuiiUo8HAAAMA2UdTY8//njMmjUrTjvttIiIOOigg+KOO+6IJ598stfndHZ2RmdnZ/f9fD7f73MCAABDV1mfnnf88cfHypUr45e//GVERDz//PPR0tISX/ziF3t9TnNzc9TV1XXfGhoaBmpcAABgCKrIyvgCoUKhEH//938f119/fVRVVUVXV1dcc801cdlll/X6nO0daWpoaIj29vbI5XIDMTYAAFAi+Xw+6urq+vTv/7I+Pe+uu+6K73//+3H77bfHEUccEc8991zMnz8/JkyYEHPnzt3uc2pqaqKmpmaAJwUAAIaqso6mSy65JC699NI466yzIiLiyCOPjFdffTWam5t7jSYAAIC+VNbXNH3wwQdRWdlzxKqqqigUCiWaCAAAGG7K+kjT6aefHtdcc00ccMABccQRR8S6deti0aJF8Zd/+ZelHg0AABgmyvqNIN577724/PLLY/ny5fHmm2/GhAkT4uyzz44rrrgiRowYsVPfoz8uBAMAAMpTf/z9X9bR1BdEEwAADB/98fd/WV/TBAAAUGqiCQAAIEE0AQAAJIgmAACABNEEAACQIJoAAAASRBMAAECCaAIAAEgQTQAAAAmiCQAAIEE0AQAAJIgmAACABNEEAACQIJoAAAASRBMAAECCaAIAAEgQTQAAAAmiCQAAIEE0ATA8dXREtLUVvwJAgmgCYHhpaYmYMydi1KiI+vri1zlzIlavLvVkAJQp0QTA8LF0acT06RH33htRKBS3FQrF+yeeGLFsWWnnA6AsiSYAhoeWloimpogsi9iypedjW7YUt3/ta444AbAN0QTA8LBoUURVVXpNVVXE4sUDMw8Ag4ZoAmDo6+iIuOeebY8wfdyWLRHLl3tzCAB6EE0ADH35/B+uYdqRQqG4HgB+TzQBMPTlchGVO/krr7KyuB4Afk80ATD01dZGzJoVUV2dXlddHXHGGcX1APB7ogmA4WHhwoiurvSarq6IBQsGZh4ABg3RBMDwcMIJEUuWRFRUbHvEqbq6uH3JkojGxtLMB0DZEk0ADB8XXBCxalXxVL2t1zhVVhbvr1pVfBwAPmYHJ3cDwBDT2Fi8dXQU3yUvl3MNEwBJogmA4am2ViwBsFOcngcAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQELZR9Prr78ef/EXfxH77LNP1NbWxpFHHhlPP/10qccCAACGiepSD5Dy29/+NhobG+OUU06J+++/P/bbb7946aWX4lOf+lSpRwMAAIaJso6m6667LhoaGuLmm2/u3jZx4sQSTgQAAAw3ZX163n/+53/GMcccE2eeeWaMHTs2jj766LjpppuSz+ns7Ix8Pt/jBgAAsLvKOpp+9atfxdKlS+Owww6LBx98MObNmxcXXXRR3Hrrrb0+p7m5Oerq6rpvDQ0NAzgxAAAw1FRkWZaVeojejBgxIo455ph4/PHHu7dddNFF8dRTT8WaNWu2+5zOzs7o7Ozsvp/P56OhoSHa29sjl8v1+8wAAEDp5PP5qKur69O//8v6SNP48ePjM5/5TI9tn/70p+O1117r9Tk1NTWRy+V63AAAAHZXWUdTY2NjbNiwoce2X/7yl3HggQeWaCIAAGC4KetoWrBgQTzxxBNx7bXXxssvvxy33357/Mu//Es0NTWVejQAAGCYKOtoOvbYY2P58uVxxx13xOTJk+Pqq6+OG264Ic4555xSjwYAAAwTZf1GEH2hPy4EAwAAytOweyMIAACAUhNNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJgJ3X0RHR1lb8CgDDhGgCYMdaWiLmzIkYNSqivr74dc6ciNWrSz0ZAPQ70QRA2tKlEdOnR9x7b0ShUNxWKBTvn3hixLJlpZ0PAPqZaAKgdy0tEU1NEVkWsWVLz8e2bClu/9rXHHECYEgTTQD0btGiiKqq9JqqqojFiwdmHgAoAdEEwPZ1dETcc8+2R5g+bsuWiOXLvTkEAEOWaAJg+/L5P1zDtCOFQnE9AAxBogmA7cvlIip38tdEZWVxPQAMQaIJgO2rrY2YNSuiujq9rro64owziusBYAgSTQD0buHCiK6u9JqurogFCwZmHgAoAdEEQO9OOCFiyZKIioptjzhVVxe3L1kS0dhYmvkAYACIJgDSLrggYtWq4ql6W69xqqws3l+1qvg4AAxhOzhRHQCieCSpsbH4tuL5fPFNH1zDBMAwIZoA2Hm1tWIJgGHH6XkAAAAJogkAACBhl6Np7ty58dhjj/XHLAAAAGVnl6Opvb09ZsyYEYcddlhce+218frrr/fHXAAAAGVhl6Pp7rvvjtdffz3mzZsXd955Zxx00EHxxS9+MX70ox/FRx991B8zAgAAlMxuXdO03377xcKFC+P555+PtWvXxqGHHhrnnntuTJgwIRYsWBAvvfRSX88JAABQEnv0RhBvvPFGrFixIlasWBFVVVXxpS99KdavXx+f+cxnYvHixX01IwAAQMnscjR99NFH8R//8R/xp3/6p3HggQfGD3/4w5g/f378+te/jltvvTUeeuihuOuuu+Jb3/pWf8wLAAAwoHb5w23Hjx8fhUIhzj777HjyySdjypQp26w55ZRTYvTo0X0wHgAAQGntcjQtXrw4zjzzzBg5cmSva0aPHh0bN27co8EAAADKwS5H07nnntsfcwAAAJSlPXojCAAAgKFONAEAACSIJgAAgATRBAAAkCCaAAAAEkQTAABAgmgCAABIEE0AAAAJogkAACBhUEXTt7/97aioqIj58+eXehQAAGCYGDTR9NRTT8X3vve9+OxnP1vqUQAAgGFkUETT+++/H+ecc07cdNNN8alPfSq5trOzM/L5fI8bAADA7hoU0dTU1BSnnXZazJgxY4drm5ubo66urvvW0NAwABMCAABDVdlH0w9+8IN49tlno7m5eafWX3bZZdHe3t5927RpUz9PCAAADGXVpR4gZdOmTXHxxRfHihUrYuTIkTv1nJqamqipqennyQAAgOGiIsuyrNRD9Obuu++OM844I6qqqrq3dXV1RUVFRVRWVkZnZ2ePx7Ynn89HXV1dtLe3Ry6X6++RAQCAEuqPv//L+kjTqaeeGuvXr++x7bzzzovDDz88vvnNb+4wmAAAAPZUWUfT3nvvHZMnT+6xba+99op99tlnm+0AAAD9oezfCAIAAKCUyvpI0/Y88sgjpR4BAAAYRhxpAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgoayjqbm5OY499tjYe++9Y+zYsTF79uzYsGFDqccCAACGkbKOpkcffTSampriiSeeiBUrVsRHH30UX/jCF2Lz5s2lHg0AABgmKrIsy0o9xM566623YuzYsfHoo4/G9OnTd+o5+Xw+6urqor29PXK5XD9PCAAAlFJ//P1f3SffZYC0t7dHRMSYMWN6XdPZ2RmdnZ3d9/P5fL/PBQAADF1lfXre/1coFGL+/PnR2NgYkydP7nVdc3Nz1NXVdd8aGhoGcEoAAGCoGTSn582bNy/uv//+aGlpif3337/Xdds70tTQ0OD0PAAAGAaG7el5F154Ydx3333x2GOPJYMpIqKmpiZqamoGaDKAPtLREZHPR+RyEbW1pZ4GAPh/yvr0vCzL4sILL4zly5fHww8/HBMnTiz1SAB9q6UlYs6ciFGjIurri1/nzIlYvbrUkwEAv1fW0dTU1BT//u//Hrfffnvsvffe0draGq2trdHR0VHq0QD23NKlEdOnR9x7b0ShUNxWKBTvn3hixLJlpZ0PAIiIMr+mqaKiYrvbb7755vjKV76yU9/DW44DZamlpRhMqX+CKyoiVq2KaGwcuLkAYJAbdtc0lXHPAeyZRYsiqqoitmzpfU1VVcTixaIJAEqsrE/PAxiSOjoi7rknHUwRxceXLy+uBwBKRjQBDLR8/g/XMO1IoVBcDwCUjGgCGGi5XETlTv7zW1lZXA8AlIxoAhhotbURs2ZFVO/gstLq6ogzzvC5TQBQYqIJoBQWLozo6kqv6eqKWLBgYOYBAHolmgBK4YQTIpYsKb6t+MePOFVXF7cvWeKd8wCgDIgmgFK54ILi5zDNmvWHa5wqK4v3V60qPg4AlFxZf04TwJDX2Fi8dXQU3yUvl3MNEwCUGdEEUA5qa8USAJQpp+cBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBQ1dHR0RbW/ErAMBuEk3A0NPSEjFnTsSoURH19cWvc+ZErF5d6skAgEFINAFDy9KlEdOnR9x7b0ShUNxWKBTvn3hixLJlpZ0PABh0BkU03XjjjXHQQQfFyJEjY+rUqfHkk0+WeiSgHLW0RDQ1RWRZxJYtPR/bsqW4/Wtfc8QJANglZR9Nd955ZyxcuDCuvPLKePbZZ+Ooo46KmTNnxptvvlnq0YBys2hRRFVVek1VVcTixQMzDwAwJFRkWZaVeoiUqVOnxrHHHhv//M//HBERhUIhGhoa4m//9m/j0ksv3WZ9Z2dndHZ2dt/P5/PR0NAQ7e3tkcvlBmxuYIB1dBSvXdp6Sl5KZWXE++9H1Nb2/1wAwIDK5/NRV1fXp3//l/WRpg8//DCeeeaZmDFjRve2ysrKmDFjRqxZs2a7z2lubo66urruW0NDw0CNC5RSPr9zwRRRXJfP9+88AMCQUdbR9Jvf/Ca6urpi3LhxPbaPGzcuWltbt/ucyy67LNrb27tvmzZtGohRgVLL5YpHkHZGZWVxPQDATijraNodNTU1kcvletyAYaC2NmLWrIjq6vS66uqIM85wah4AsNPKOpr23XffqKqqira2th7b29raor6+vkRTAWVr4cKIrq70mq6uiAULBmYeAGBIKOtoGjFiRHz+85+PlStXdm8rFAqxcuXKmDZtWgknA8rSCSdELFkSUVGx7RGn6uri9iVLIhobSzMfADAolXU0RUQsXLgwbrrpprj11lvjxRdfjHnz5sXmzZvjvPPOK/VoQDm64IKIVauKp+ptvcapsrJ4f9Wq4uMAALtgByf/l96Xv/zleOutt+KKK66I1tbWmDJlSjzwwAPbvDkEQLfGxuKto6P4Lnm5nGuYAIDdVvaf07Sn+uN92gEAgPI07D6nCQAAoNREEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAICE6lIP0N+yLIuIiHw+X+JJAACA/rb17/6tHdAXhnw0vf322xER0dDQUOJJAACAgfL2229HXV1dn3yvIR9NY8aMiYiI1157rc/+S2PwyOfz0dDQEJs2bYpcLlfqcRhg9v/wZv8Pb/b/8Gb/D2/t7e1xwAEHdHdAXxjy0VRZWbxsq66uzotmGMvlcvb/MGb/D2/2//Bm/w9v9v/wtrUD+uR79dl3AgAAGIJEEwAAQMKQj6aampq48soro6amptSjUAL2//Bm/w9v9v/wZv8Pb/b/8NYf+78i68v34gMAABhihvyRJgAAgD0hmgAAABJEEwAAQIJoAgAASBiS0XTNNdfE8ccfH5/85Cdj9OjRO/WcLMviiiuuiPHjx0dtbW3MmDEjXnrppf4dlH7xzjvvxDnnnBO5XC5Gjx4dX/3qV+P9999PPufkk0+OioqKHrcLLrhggCZmT9x4441x0EEHxciRI2Pq1Knx5JNPJtf/8Ic/jMMPPzxGjhwZRx55ZPzkJz8ZoEnpD7uy/2+55ZZtXucjR44cwGnpK4899licfvrpMWHChKioqIi77757h8955JFH4nOf+1zU1NTEoYceGrfccku/z0n/2NX9/8gjj2zz2q+oqIjW1taBGZg+1dzcHMcee2zsvffeMXbs2Jg9e3Zs2LBhh8/b09//QzKaPvzwwzjzzDNj3rx5O/2c66+/Pr773e/GsmXLYu3atbHXXnvFzJkz43e/+10/Tkp/OOecc+KFF16IFStWxH333RePPfZYnH/++Tt83l//9V/HG2+80X27/vrrB2Ba9sSdd94ZCxcujCuvvDKeffbZOOqoo2LmzJnx5ptvbnf9448/HmeffXZ89atfjXXr1sXs2bNj9uzZ8fOf/3yAJ6cv7Or+j4jI5XI9XuevvvrqAE5MX9m8eXMcddRRceONN+7U+o0bN8Zpp50Wp5xySjz33HMxf/78+Ku/+qt48MEH+3lS+sOu7v+tNmzY0OP1P3bs2H6akP706KOPRlNTUzzxxBOxYsWK+Oijj+ILX/hCbN68udfn9Mnv/2wIu/nmm7O6urodrisUCll9fX32j//4j93b3n333aympia74447+nFC+tovfvGLLCKyp556qnvb/fffn1VUVGSvv/56r8876aSTsosvvngAJqQvHXfccVlTU1P3/a6urmzChAlZc3Pzdtf/2Z/9WXbaaaf12DZ16tTsb/7mb/p1TvrHru7/nf2dwOASEdny5cuTa77xjW9kRxxxRI9tX/7yl7OZM2f242QMhJ3Z/z/96U+ziMh++9vfDshMDKw333wzi4js0Ucf7XVNX/z+H5JHmnbVxo0bo7W1NWbMmNG9ra6uLqZOnRpr1qwp4WTsqjVr1sTo0aPjmGOO6d42Y8aMqKysjLVr1yaf+/3vfz/23XffmDx5clx22WXxwQcf9Pe47IEPP/wwnnnmmR6v28rKypgxY0avr9s1a9b0WB8RMXPmTK/zQWh39n9ExPvvvx8HHnhgNDQ0xKxZs+KFF14YiHEpMa99IiKmTJkS48ePjz/+4z+O1atXl3oc+kh7e3tERIwZM6bXNX3xb0D17o03tGw9p3XcuHE9to8bN875roNMa2vrNofbq6urY8yYMcl9+ed//udx4IEHxoQJE+JnP/tZfPOb34wNGzbEj3/84/4emd30m9/8Jrq6urb7uv3v//7v7T6ntbXV63yI2J39P2nSpPi3f/u3+OxnPxvt7e3xne98J44//vh44YUXYv/99x+IsSmR3l77+Xw+Ojo6ora2tkSTMRDGjx8fy5Yti2OOOSY6OzvjX//1X+Pkk0+OtWvXxuc+97lSj8ceKBQKMX/+/GhsbIzJkyf3uq4vfv8Pmmi69NJL47rrrkuuefHFF+Pwww8foIkYSDu7/3fX/7/m6cgjj4zx48fHqaeeGq+88koccsghu/19gfIxbdq0mDZtWvf9448/Pj796U/H9773vbj66qtLOBnQnyZNmhSTJk3qvn/88cfHK6+8EosXL47bbruthJOxp5qamuLnP/95tLS09Pt/1qCJpq9//evxla98Jbnm4IMP3q3vXV9fHxERbW1tMX78+O7tbW1tMWXKlN36nvStnd3/9fX121wEvmXLlnjnnXe69/POmDp1akREvPzyy6KpTO27775RVVUVbW1tPba3tbX1uq/r6+t3aT3la3f2/8d94hOfiKOPPjpefvnl/hiRMtLbaz+XyznKNEwdd9xxA/KHNv3nwgsv7H7Drx2dLdAXv/8HzTVN++23Xxx++OHJ24gRI3bre0+cODHq6+tj5cqV3dvy+XysXbu2x/8rSens7P6fNm1avPvuu/HMM890P/fhhx+OQqHQHUI747nnnouI6BHRlJcRI0bE5z//+R6v20KhECtXruz1dTtt2rQe6yMiVqxY4XU+CO3O/v+4rq6uWL9+vdf5MOC1z8c999xzXvuDVJZlceGFF8by5cvj4YcfjokTJ+7wOX3yb8DuvlNFOXv11VezdevWZVdddVU2atSobN26ddm6deuy9957r3vNpEmTsh//+Mfd97/97W9no0ePzu65557sZz/7WTZr1qxs4sSJWUdHRyl+BPbAn/zJn2RHH310tnbt2qylpSU77LDDsrPPPrv78f/93//NJk2alK1duzbLsix7+eWXs29961vZ008/nW3cuDG75557soMPPjibPn16qX4EdtIPfvCDrKamJrvllluyX/ziF9n555+fjR49Omttbc2yLMvOPffc7NJLL+1ev3r16qy6ujr7zne+k7344ovZlVdemX3iE5/I1q9fX6ofgT2wq/v/qquuyh588MHslVdeyZ555pnsrLPOykaOHJm98MILpfoR2E3vvfde9+/2iMgWLVqUrVu3Lnv11VezLMuySy+9NDv33HO71//qV7/KPvnJT2aXXHJJ9uKLL2Y33nhjVlVVlT3wwAOl+hHYA7u6/xcvXpzdfffd2UsvvZStX78+u/jii7PKysrsoYceKtWPwB6YN29eVldXlz3yyCPZG2+80X374IMPutf0x+//IRlNc+fOzSJim9tPf/rT7jURkd18883d9wuFQnb55Zdn48aNy2pqarJTTz0127Bhw8APzx57++23s7PPPjsbNWpUlsvlsvPOO69HMG/cuLHH/x5ee+21bPr06dmYMWOympqa7NBDD80uueSSrL29vUQ/Abvin/7pn7IDDjggGzFiRHbcccdlTzzxRPdjJ510UjZ37twe6++6667sj/7oj7IRI0ZkRxxxRPZf//VfAzwxfWlX9v/8+fO7144bNy770pe+lD377LMlmJo9tfUtpD9+27q/586dm5100knbPGfKlCnZiBEjsoMPPrjH3wAMLru6/6+77rrskEMOyUaOHJmNGTMmO/nkk7OHH364NMOzx7a37z/+d31//P6v+P1/OAAAANsxaK5pAgAAKAXRBAAAkCCaAAAAEkQTAABAgmgCAABIEE0AAAAJogkAACBBNAEAACSIJgAAgATRBAAAkCCaAAAAEkQTAEPGW2+9FfX19XHttdd2b3v88cdjxIgRsXLlyhJOBsBgVpFlWVbqIQCgr/zkJz+J2bNnx+OPPx6TJk2KKVOmxKxZs2LRokWlHg2AQUo0ATDkNDU1xUMPPRTHHHNMrF+/Pp566qmoqakp9VgADFKiCYAhp6OjIyZPnhybNm2KZ555Jo488shSjwTAIOaaJgCGnFdeeSV+/etfR6FQiP/5n/8p9TgADHKONAEwpHz44Ydx3HHHxZQpU2LSpElxww03xPr162Ps2LGlHg2AQUo0ATCkXHLJJfGjH/0onn/++Rg1alScdNJJUVdXF/fdd1+pRwNgkHJ6HgBDxiOPPBI33HBD3HbbbZHL5aKysjJuu+22WLVqVSxdurTU4wEwSDnSBAAAkOBIEwAAQIJoAgAASBBNAAAACaIJAAAgQTQBAAAkiCYAAIAE0QQAAJAgmgAAABJEEwAAQIJoAgAASBBNAAAACf8HbNgFIqcCnC8AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data(X1, y, xlabel=\"x\", ylabel=\"y\")\n"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"scrolled": true,
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f428364a290>]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data(X1, y, xlabel=\"x\", ylabel=\"y\")\n",
"theta_start = np.matrix([0, 0]).reshape(2, 1)\n",
"theta, _ = gradient_descent(cost, gradient, theta_start, X1, y, eps=0.00001)\n",
"plot_fun(fig, polynomial_regression(theta), X1)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"Ten model ma duże **obciążenie** (**błąd systematyczny**, *bias*) zachodzi **niedostateczne dopasowanie** (*underfitting*)."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f42157242e0>]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data(X2, y, xlabel=\"x\", ylabel=\"y\")\n",
"theta_start = np.matrix([0, 0, 0]).reshape(3, 1)\n",
"theta, _ = gradient_descent(cost, gradient, theta_start, X2, y, eps=0.000001)\n",
"plot_fun(fig, polynomial_regression(theta), X1)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Ten model jest odpowiednio dopasowany."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7f421483cd60>]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 960x540 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plot_data(X5, y, xlabel=\"x\", ylabel=\"y\")\n",
"theta_start = np.matrix([0, 0, 0, 0, 0, 0]).reshape(6, 1)\n",
"theta, _ = gradient_descent(cost, gradient, theta_start, X5, y, alpha=0.5, eps=10**-7)\n",
"plot_fun(fig, polynomial_regression(theta), X1)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"Ten model ma dużą **wariancję** (*variance*) zachodzi **nadmierne dopasowanie** (*overfitting*)."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"(Zwróć uwagę na dziwny kształt krzywej w lewej części wykresu to m.in. efekt nadmiernego dopasowania)."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Nadmierne dopasowanie występuje, gdy model ma zbyt dużo stopni swobody w stosunku do ilości danych wejściowych.\n",
"\n",
"Jest to zjawisko niepożądane.\n",
"\n",
"Możemy obrazowo powiedzieć, że nadmierne dopasowanie występuje, gdy model zaczyna modelować szum/zakłócenia w danych zamiast ich „głównego nurtu”. "
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Zobacz też: https://pl.wikipedia.org/wiki/Nadmierne_dopasowanie"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"<img style=\"margin:auto\" width=\"90%\" src=\"fit.png\"/>"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Obciążenie (błąd systematyczny, *bias*)\n",
"\n",
"* Wynika z błędnych założeń co do algorytmu uczącego się.\n",
"* Duże obciążenie powoduje niedostateczne dopasowanie."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Wariancja (*variance*)\n",
"\n",
"* Wynika z nadwrażliwości na niewielkie fluktuacje w zbiorze uczącym.\n",
"* Wysoka wariancja może spowodować nadmierne dopasowanie (modelując szum zamiast sygnału)."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"<img style=\"margin:auto\" width=\"40%\" src=\"bias2.png\"/>"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"<img style=\"margin:auto\" width=\"60%\" src=\"curves.jpg\"/>"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 6.3. Regularyzacja"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def SGD(\n",
" h,\n",
" fJ,\n",
" fdJ,\n",
" theta,\n",
" X,\n",
" Y,\n",
" alpha=0.001,\n",
" maxEpochs=1.0,\n",
" batchSize=100,\n",
" adaGrad=False,\n",
" logError=False,\n",
" validate=0.0,\n",
" valStep=100,\n",
" lamb=0,\n",
" trainsetsize=1.0,\n",
"):\n",
" \"\"\"Stochastic Gradient Descent - stochastyczna wersja metody gradientu prostego\n",
" (więcej na ten temat na następnym wykładzie)\n",
" \"\"\"\n",
" errorsX, errorsY = [], []\n",
" errorsVX, errorsVY = [], []\n",
"\n",
" XT, YT = X, Y\n",
"\n",
" m_end = int(trainsetsize * len(X))\n",
"\n",
" if validate > 0:\n",
" mv = int(X.shape[0] * validate)\n",
" XV, YV = X[:mv], Y[:mv]\n",
" XT, YT = X[mv:m_end], Y[mv:m_end]\n",
" m, n = XT.shape\n",
"\n",
" start, end = 0, batchSize\n",
" maxSteps = (m * float(maxEpochs)) / batchSize\n",
"\n",
" if adaGrad:\n",
" hgrad = np.matrix(np.zeros(n)).reshape(n, 1)\n",
"\n",
" for i in range(int(maxSteps)):\n",
" XBatch, YBatch = XT[start:end, :], YT[start:end, :]\n",
"\n",
" grad = fdJ(h, theta, XBatch, YBatch, lamb=lamb)\n",
" if adaGrad:\n",
" hgrad += np.multiply(grad, grad)\n",
" Gt = 1.0 / (10**-7 + np.sqrt(hgrad))\n",
" theta = theta - np.multiply(alpha * Gt, grad)\n",
" else:\n",
" theta = theta - alpha * grad\n",
"\n",
" if logError:\n",
" errorsX.append(float(i * batchSize) / m)\n",
" errorsY.append(fJ(h, theta, XBatch, YBatch).item())\n",
" if validate > 0 and i % valStep == 0:\n",
" errorsVX.append(float(i * batchSize) / m)\n",
" errorsVY.append(fJ(h, theta, XV, YV).item())\n",
"\n",
" if start + batchSize < m:\n",
" start += batchSize\n",
" else:\n",
" start = 0\n",
" end = min(start + batchSize, m)\n",
" return theta, (errorsX, errorsY, errorsVX, errorsVY)\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"# Przygotowanie danych do przykładu regularyzacji\n",
"\n",
"n = 6\n",
"\n",
"data = np.matrix(np.loadtxt(\"ex2data2.txt\", delimiter=\",\"))\n",
"np.random.shuffle(data)\n",
"\n",
"X = powerme(data[:, 0], data[:, 1], n)\n",
"Y = data[:, 2]\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def draw_regularization_example(\n",
" X, Y, lamb=0, alpha=1, adaGrad=True, maxEpochs=2500, validate=0.25\n",
"):\n",
" \"\"\"Rusuje przykład regularyzacji\"\"\"\n",
" plt.figure(figsize=(16, 8))\n",
" plt.subplot(121)\n",
" plt.scatter(\n",
" X[:, 2].tolist(),\n",
" X[:, 1].tolist(),\n",
" c=Y.tolist(),\n",
" s=100,\n",
" cmap=plt.cm.get_cmap(\"prism\"),\n",
" )\n",
"\n",
" theta = np.matrix(np.zeros(X.shape[1])).reshape(X.shape[1], 1)\n",
" thetaBest, err = SGD(\n",
" h,\n",
" J,\n",
" dJ,\n",
" theta,\n",
" X,\n",
" Y,\n",
" alpha=alpha,\n",
" adaGrad=adaGrad,\n",
" maxEpochs=maxEpochs,\n",
" batchSize=100,\n",
" logError=True,\n",
" validate=validate,\n",
" valStep=1,\n",
" lamb=lamb,\n",
" )\n",
"\n",
" xx, yy = np.meshgrid(np.arange(-1.5, 1.5, 0.02), np.arange(-1.5, 1.5, 0.02))\n",
" l = len(xx.ravel())\n",
" C = powerme(xx.reshape(l, 1), yy.reshape(l, 1), n)\n",
" z = classifyBi(thetaBest, C).reshape(int(np.sqrt(l)), int(np.sqrt(l)))\n",
"\n",
" plt.contour(xx, yy, z, levels=[0.5], lw=3)\n",
" plt.ylim(-1, 1.2)\n",
" plt.xlim(-1, 1.2)\n",
" plt.legend()\n",
" plt.subplot(122)\n",
" plt.plot(err[0], err[1], lw=3, label=\"Training error\")\n",
" if validate > 0:\n",
" plt.plot(err[2], err[3], lw=3, label=\"Validation error\")\n",
" plt.legend()\n",
" plt.ylim(0.2, 0.8)\n"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"scrolled": true,
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_3088/2678993393.py:5: RuntimeWarning: overflow encountered in exp\n",
" y = 1.0 / (1.0 + np.exp(-x))\n",
"/tmp/ipykernel_3088/2651435526.py:38: UserWarning: The following kwargs were not used by contour: 'lw'\n",
" plt.contour(xx, yy, z, levels=[0.5], lw=3)\n",
"No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 1600x800 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"draw_regularization_example(X, Y)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Regularyzacja\n",
"\n",
"Regularyzacja jest metodą zapobiegania zjawisku nadmiernego dopasowania (*overfitting*) poprzez odpowiednie zmodyfikowanie funkcji kosztu.\n",
"\n",
"Do funkcji kosztu dodawane jest specjalne wyrażenie (**wyrażenie regularyzacyjne** zaznaczone na czerwono w poniższych wzorach), będące „karą” za ekstremalne wartości parametrów $\\theta$.\n",
"\n",
"W ten sposób preferowane są wektory $\\theta$ z mniejszymi wartosciami parametrów mają automatycznie niższy koszt.\n",
"\n",
"Jak silną regularyzację chcemy zastosować? Możemy o tym zadecydować, dobierajac odpowiednio **parametr regularyzacji** $\\lambda$."
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"source": [
"Przedstawiona tu metoda regularyzacji to tzw. metoda L2 (*ridge*). Istnieją również inne metody regularyzacji, które charakteryzują się trochę innymi własnościami, np. L2 (*lasso*) lub *elastic net*. Więcej na ten temat można przeczytać np. tu:\n",
"* [L1 and L2 Regularization Methods](https://towardsdatascience.com/l1-and-l2-regularization-methods-ce25e7fc831c)\n",
"* [Ridge and Lasso Regression: L1 and L2 Regularization](https://towardsdatascience.com/ridge-and-lasso-regression-a-complete-guide-with-python-scikit-learn-e20e34bcbf0b)\n",
"* [Elastic Net Regression](https://towardsdatascience.com/elastic-net-regression-from-sklearn-to-tensorflow-3b48eee45e91)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Regularyzacja dla regresji liniowej funkcja kosztu\n",
"\n",
"$$\n",
"J(\\theta) \\, = \\, \\dfrac{1}{2m} \\left( \\displaystyle\\sum_{i=1}^{m} h_\\theta(x^{(i)}) - y^{(i)} \\color{red}{ + \\lambda \\displaystyle\\sum_{j=1}^{n} \\theta^2_j } \\right)\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"source": [
"* $\\lambda$ parametr regularyzacji\n",
"* jeżeli $\\lambda$ jest zbyt mały, skutkuje to nadmiernym dopasowaniem\n",
"* jeżeli $\\lambda$ jest zbyt duży, skutkuje to niedostatecznym dopasowaniem"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Regularyzacja dla regresji liniowej gradient\n",
"\n",
"$$\\small\n",
"\\begin{array}{llll}\n",
"\\dfrac{\\partial J(\\theta)}{\\partial \\theta_0} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_0 & \\textrm{dla $j = 0$ }\\\\\n",
"\\dfrac{\\partial J(\\theta)}{\\partial \\theta_j} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_j \\color{red}{+ \\dfrac{\\lambda}{m}\\theta_j} & \\textrm{dla $j = 1, 2, \\ldots, n $} \\\\\n",
"\\end{array} \n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Regularyzacja dla regresji logistycznej funkcja kosztu\n",
"\n",
"$$\n",
"\\begin{array}{rtl}\n",
"J(\\theta) & = & -\\dfrac{1}{m} \\left( \\displaystyle\\sum_{i=1}^{m} y^{(i)} \\log h_\\theta(x^{(i)}) + \\left( 1-y^{(i)} \\right) \\log \\left( 1-h_\\theta(x^{(i)}) \\right) \\right) \\\\\n",
"& & \\color{red}{ + \\dfrac{\\lambda}{2m} \\displaystyle\\sum_{j=1}^{n} \\theta^2_j } \\\\\n",
"\\end{array}\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Regularyzacja dla regresji logistycznej gradient\n",
"\n",
"$$\\small\n",
"\\begin{array}{llll}\n",
"\\dfrac{\\partial J(\\theta)}{\\partial \\theta_0} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_0 & \\textrm{dla $j = 0$ }\\\\\n",
"\\dfrac{\\partial J(\\theta)}{\\partial \\theta_j} &=& \\dfrac{1}{m}\\displaystyle\\sum_{i=1}^m \\left( h_{\\theta}(x^{(i)})-y^{(i)} \\right) x^{(i)}_j \\color{red}{+ \\dfrac{\\lambda}{m}\\theta_j} & \\textrm{dla $j = 1, 2, \\ldots, n $} \\\\\n",
"\\end{array} \n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"### Implementacja metody regularyzacji"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [],
"source": [
"def J_(h, theta, X, y, lamb=0):\n",
" \"\"\"Funkcja kosztu z regularyzacją\"\"\"\n",
" m = float(len(y))\n",
" f = h(theta, X, eps=10**-7)\n",
" j = 1.0 / m * -np.sum(\n",
" np.multiply(y, np.log(f)) + np.multiply(1 - y, np.log(1 - f)), axis=0\n",
" ) + lamb / (2 * m) * np.sum(np.power(theta[1:], 2))\n",
" return j\n",
"\n",
"\n",
"def dJ_(h, theta, X, y, lamb=0):\n",
" \"\"\"Gradient funkcji kosztu z regularyzacją\"\"\"\n",
" m = float(y.shape[0])\n",
" g = 1.0 / y.shape[0] * (X.T * (h(theta, X) - y))\n",
" g[1:] += lamb / m * theta[1:]\n",
" return g\n"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"slider_lambda = widgets.FloatSlider(\n",
" min=0.0, max=0.5, step=0.005, value=0.01, description=r\"$\\lambda$\", width=300\n",
")\n",
"\n",
"\n",
"def slide_regularization_example_2(lamb):\n",
" draw_regularization_example(X, Y, lamb=lamb)\n"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"scrolled": false,
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3bab505ae15548059e1037eda3e1d9f8",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"interactive(children=(FloatSlider(value=0.01, description='$\\\\lambda$', max=0.5, step=0.005), Button(descripti…"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<function __main__.slide_regularization_example_2(lamb)>"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"widgets.interact_manual(slide_regularization_example_2, lamb=slider_lambda)\n"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def cost_lambda_fun(lamb):\n",
" \"\"\"Koszt w zależności od parametru regularyzacji lambda\"\"\"\n",
" theta = np.matrix(np.zeros(X.shape[1])).reshape(X.shape[1], 1)\n",
" thetaBest, err = SGD(\n",
" h,\n",
" J,\n",
" dJ,\n",
" theta,\n",
" X,\n",
" Y,\n",
" alpha=1,\n",
" adaGrad=True,\n",
" maxEpochs=2500,\n",
" batchSize=100,\n",
" logError=True,\n",
" validate=0.25,\n",
" valStep=1,\n",
" lamb=lamb,\n",
" )\n",
" return err[1][-1], err[3][-1]\n",
"\n",
"\n",
"def plot_cost_lambda():\n",
" \"\"\"Wykres kosztu w zależności od parametru regularyzacji lambda\"\"\"\n",
" plt.figure(figsize=(16, 8))\n",
" ax = plt.subplot(111)\n",
" Lambda = np.arange(0.0, 1.0, 0.01)\n",
" Costs = [cost_lambda_fun(lamb) for lamb in Lambda]\n",
" CostTrain = [cost[0] for cost in Costs]\n",
" CostCV = [cost[1] for cost in Costs]\n",
" plt.plot(Lambda, CostTrain, lw=3, label=\"training error\")\n",
" plt.plot(Lambda, CostCV, lw=3, label=\"validation error\")\n",
" ax.set_xlabel(r\"$\\lambda$\")\n",
" ax.set_ylabel(\"cost\")\n",
" plt.legend()\n",
" plt.ylim(0.2, 0.8)\n"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 1600x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_cost_lambda()\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## 5.4. Krzywa uczenia się"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"* Krzywa uczenia pozwala sprawdzić, czy uczenie przebiega poprawnie.\n",
"* Krzywa uczenia to wykres zależności między wielkością zbioru treningowego a wartością funkcji kosztu.\n",
"* Wraz ze wzrostem wielkości zbioru treningowego wartość funkcji kosztu na zbiorze treningowym rośnie.\n",
"* Wraz ze wzrostem wielkości zbioru treningowego wartość funkcji kosztu na zbiorze walidacyjnym maleje."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"slideshow": {
"slide_type": "notes"
}
},
"outputs": [],
"source": [
"def cost_trainsetsize_fun(m):\n",
" \"\"\"Koszt w zależności od wielkości zbioru uczącego\"\"\"\n",
" theta = np.matrix(np.zeros(X.shape[1])).reshape(X.shape[1], 1)\n",
" thetaBest, err = SGD(\n",
" h,\n",
" J,\n",
" dJ,\n",
" theta,\n",
" X,\n",
" Y,\n",
" alpha=1,\n",
" adaGrad=True,\n",
" maxEpochs=2500,\n",
" batchSize=100,\n",
" logError=True,\n",
" validate=0.25,\n",
" valStep=1,\n",
" lamb=0.01,\n",
" trainsetsize=m,\n",
" )\n",
" return err[1][-1], err[3][-1]\n",
"\n",
"\n",
"def plot_learning_curve():\n",
" \"\"\"Wykres krzywej uczenia się\"\"\"\n",
" plt.figure(figsize=(16, 8))\n",
" ax = plt.subplot(111)\n",
" M = np.arange(0.3, 1.0, 0.05)\n",
" Costs = [cost_trainsetsize_fun(m) for m in M]\n",
" CostTrain = [cost[0] for cost in Costs]\n",
" CostCV = [cost[1] for cost in Costs]\n",
" plt.plot(M, CostTrain, lw=3, label=\"training error\")\n",
" plt.plot(M, CostCV, lw=3, label=\"validation error\")\n",
" ax.set_xlabel(\"trainset size\")\n",
" ax.set_ylabel(\"cost\")\n",
" plt.legend()\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Krzywa uczenia a obciążenie i wariancja\n",
"\n",
"Wykreślenie krzywej uczenia pomaga diagnozować nadmierne i niedostateczne dopasowanie:\n",
"\n",
"<img width=\"100%\" src=\"learning-curves.png\"/>\n",
"\n",
"Źródło: http://www.ritchieng.com/machinelearning-learning-curve"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 1600x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_learning_curve()\n"
]
}
],
"metadata": {
"celltoolbar": "Slideshow",
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
},
"livereveal": {
"start_slideshow_at": "selected",
"theme": "white"
}
},
"nbformat": 4,
"nbformat_minor": 4
}