Merge git.wmi.amu.edu.pl:filipg/aitech-eks

cw/08_regresja_logistyczna.ipynb

@@ -507,11 +507,7 @@
     "        acc_score += torch.sum((Y_predictions > 0.5) == Y).item()\n",
     "        items_total += Y.shape[0] \n",
     "\n",
-    "        optimizer.zero_grad()\n",
     "        loss = criterion(Y_predictions, Y)\n",
-    "        loss.backward()\n",
-    "        optimizer.step()\n",
-    "\n",
     "\n",
     "        loss_score += loss.item() * Y.shape[0] \n",
     "    return (loss_score / items_total), (acc_score / items_total)"

cw/08_regresja_logistyczna_ODPOWIEDZI.ipynb

@@ -699,11 +699,7 @@
     "        acc_score += torch.sum((Y_predictions > 0.5) == Y).item()\n",
     "        items_total += Y.shape[0] \n",
     "\n",
-    "        optimizer.zero_grad()\n",
     "        loss = criterion(Y_predictions, Y)\n",
-    "        loss.backward()\n",
-    "        optimizer.step()\n",
-    "\n",
     "\n",
     "        loss_score += loss.item() * Y.shape[0] \n",
     "    return (loss_score / items_total), (acc_score / items_total)"

wyk/08_Regresja_liniowa.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "continent-intermediate",
+   "id": "cathedral-newark",
    "metadata": {},
    "source": [
     "# Regresja liniowa\n",
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "original-speed",
+   "id": "heard-clinton",
    "metadata": {},
    "source": [
     "Regresje liniowa (jednej zmiennej) jest łatwa do rozwiązania — wystarczy podstawić do wzoru!\n",
@@ -43,7 +43,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "significant-relaxation",
+   "id": "preceding-impression",
    "metadata": {},
    "source": [
     "## Regresja wielu zmiennych\n",
@@ -53,31 +53,45 @@
     "\n",
     "Cena mieszkań może być prognozowana na podstawie:\n",
     "\n",
-    "* powierzchni ($x_1 = 32.3$) \n",
+    "* powierzchni w m$^2$ ($x_1 = 32.3$) $w_1 = 7000$\n",
     "\n",
-    "* liczby pokoi ($x_2 = 3$)\n",
+    "* liczby pokoi ($x_2 = 3$) $w_2 = -30000$\n",
     " \n",
-    "* piętra ($x_3 = 4$)\n",
+    "* nr piętra ($x_3 = 4$) \n",
     "\n",
-    "* wieku ($x_4 = 13$)\n",
+    "* wieku ($x_4 = 13$) $w_3 = -1000$\n",
     "\n",
     "* odległości od Dworca Centralnego w Warszawie ($x_5 = 371.3$)\n",
     "\n",
+    "* wielkość miasta\n",
+    "\n",
+    "* gęstość zaludnienia\n",
+    "\n",
     "* cech zerojedynkowych:\n",
     "\n",
     "  * czy wielka płyta? ($x_6 = 0$)\n",
     "\n",
-    "  * czy jest jacuzzi? ($x_7 = 1$)\n",
+    "  * czy jest jacuzzi? ($x_7 = 1$)  $w_7 = 5000$\n",
     "\n",
-    "  * czy jest grzyb? ($x_8 = 0$)\n",
+    "  * czy jest grzyb? ($x_8 = 0$) $w_8 = -40000$\n",
     " \n",
     "  * czy to Kielce? ($x_9 = 1$)\n",
     "  \n",
-    "* ...\n",
+    "  * czy to Kraków ($x_{10} = 0$)\n",
+    "  \n",
+    "  * czy to Katowice ($x_{11} = 0$)\n",
+    "   \n",
+    "  * czy obok budynku jest parking \n",
+    "  \n",
+    "  * czy w budynku jest parking\n",
+    "\n",
+    "* zakodowany opis \n",
+    "\n",
+    "  * $(x_{12}, x_{|V|+12})$ - wektor tf-idf \n",
     "\n",
     "... więc uogólniamy na wiele ($k$) wymiarów:\n",
     "\n",
-    "$$ y = w_0 + w_1x_1 + \\ldots + w_kx_k = w_0 + \\sum_{j=1}^{k} w_jx_j $$\n",
+    "$$ y = w_0 + w_1x_1 + \\ldots + w_kx_k = w_0 + \\sum_{j=1}^{k} w_jx_j = w_0 + \\vec{w}\\vec{x}$$\n",
     "\n",
     "gdzie:\n",
     "\n",
@@ -97,10 +111,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ordinary-appendix",
+   "id": "confused-increase",
    "metadata": {},
    "source": [
-    "## Kilka sporzeżeń\n",
+    "## Kilka spostrzeżeń\n",
     "\n",
     "Regresja liniowa to najprostszy możliwy model:\n",
     "\n",
@@ -114,7 +128,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "egyptian-austria",
+   "id": "freelance-controversy",
    "metadata": {},
    "source": [
     "## Uczenie\n",
@@ -148,7 +162,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "exact-train",
+   "id": "divine-medium",
    "metadata": {},
    "source": [
     "## Ewaluacja regresji\n",
@@ -171,7 +185,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "selective-agriculture",
+   "id": "supreme-tennessee",
    "metadata": {},
    "source": [
     "## Regresja liniowa dla tekstu\n",
@@ -181,10 +195,84 @@
     "![schemat regresji liniowej](08_files/regresja-liniowa-tekst.png)\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "seasonal-syndication",
+   "metadata": {},
+   "source": [
+    "### Przykład \n",
+    "\n",
+    "Wyzwanie RetroC2 - odgadywanie roku dla krótkiego tekstu (1814-2013), <https://gonito.net/challenge/retroc2>.\n",
+    "    \n",
+    "Lista słów (obcięta do 7 znaków) z największą/najmniejszymi wagami.   \n",
+    "\n",
+    "```\n",
+    "wzbudze -0.08071490\n",
+    "paczka  -0.08000180\n",
+    "szarpi  -0.05906200\n",
+    "spadoch -0.05784140\n",
+    "rzymsko -0.05466660\n",
+    "sosnowy -0.05162170\n",
+    "dębowyc -0.04778910\n",
+    "nawinię -0.04649400\n",
+    "odmówie -0.04522140\n",
+    "zacisko -0.04480620\n",
+    "funkcją -0.04479500\n",
+    "werben  -0.04423350\n",
+    "nieumyś -0.04415200\n",
+    "wodomie -0.04351570\n",
+    "szczote -0.04313390\n",
+    "exekucy -0.04297940\n",
+    "listew  -0.04214090\n",
+    "daley   -0.04145400\n",
+    "metro   -0.04080110\n",
+    "wyjąwsz -0.04078060\n",
+    "salda   -0.04042050\n",
+    "tkach   -0.04020180\n",
+    "cetnar  -0.03999050\n",
+    "zgóry   -0.03855980\n",
+    "belek   -0.03833100\n",
+    "formier -0.03805890\n",
+    "wekslu  -0.03796510\n",
+    "odmową  -0.03753760\n",
+    "\n",
+    "odwadni 0.04662140\n",
+    "dozując 0.04672770\n",
+    "wyników 0.04744650\n",
+    "sprawst 0.04746330\n",
+    "jakub   0.04750710\n",
+    "ścieran 0.04791070\n",
+    "wrodzon 0.04799800\n",
+    "koryguj 0.04843560\n",
+    "odnotow 0.04854360\n",
+    "tłumiąc 0.04917320\n",
+    "leasing 0.04963200\n",
+    "ecznej  0.04994810\n",
+    "2013r   0.05009500\n",
+    "kompens 0.05049060\n",
+    "comarch 0.05058620\n",
+    "pojazde 0.05078540\n",
+    "badanyc 0.05340480\n",
+    "kontakc 0.05377990\n",
+    "sygnali 0.05601120\n",
+    "piasta  0.05658670\n",
+    "2000r   0.05716820\n",
+    "stropni 0.06123470\n",
+    "oszone  0.06124600\n",
+    "zamonto 0.06424310\n",
+    "………..   0.06498500\n",
+    "kumulat 0.06596770\n",
+    "faktura 0.07313080\n",
+    "wielost 0.09677770\n",
+    "wielomi 0.12307300\n",
+    "```\n",
+    "\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "numerous-limitation",
+   "id": "encouraging-martial",
    "metadata": {},
    "outputs": [],
    "source": []