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This commit is contained in:
Paweł Skórzewski 2023-11-09 17:46:13 +01:00
parent 77df141546
commit 4b07e20017
10 changed files with 1650 additions and 1687 deletions
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2
lab/01_Podstawowe_narzędzia.ipynb
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@ -2271,7 +2271,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
},
"livereveal": {
"start_slideshow_at": "selected",

2
lab/02_Wczytywanie_i_prezentowanie_danych.ipynb
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@ -928,7 +928,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
},
"livereveal": {
"start_slideshow_at": "selected",

2
lab/04_Reprezentacja_danych.ipynb
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@ -882,7 +882,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
},
"livereveal": {
"start_slideshow_at": "selected",

2
lab/05_Ewaluacja.ipynb
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@ -295,7 +295,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
},
"livereveal": {
"start_slideshow_at": "selected",

2
lab/titanic.tsv
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@ -1,4 +1,4 @@
"Survived" "PassengerId" "Pclass" "Name" "Sex" "Age" "SibSp" "Parch" "Ticket" "Fare" "Cabin" "Embarked"
"Survived" "PassengerId" "Pclass" "Name " "Sex" "Age" "SibSp" "Parch" "Ticket" "Fare" "Cabin" "Embarked"
0 530 2 "Hocking Mr. Richard George" "male" 23 2 1 "29104" 11.5 "" "S"
0 466 3 "Goncalves Mr. Manuel Estanslas" "male" 38 0 0 "SOTON/O.Q. 3101306" 7.05 "" "S"
0 753 3 "Vande Velde Mr. Johannes Joseph" "male" 33 0 0 "345780" 9.5 "" "S"

1 Survived PassengerId Pclass Name Name Sex Age SibSp Parch Ticket Fare Cabin Embarked
2 0 530 2 Hocking Mr. Richard George male 23 2 1 29104 11.5 S
3 0 466 3 Goncalves Mr. Manuel Estanslas male 38 0 0 SOTON/O.Q. 3101306 7.05 S
4 0 753 3 Vande Velde Mr. Johannes Joseph male 33 0 0 345780 9.5 S

2
wyk/01_Wprowadzenie.ipynb
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@ -543,7 +543,7 @@
"name": "python",
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"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
},
"livereveal": {
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3206
wyk/02_Regresja_liniowa_1.ipynb
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wyk/03_Regresja_liniowa_2.ipynb
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2
wyk/04_Regresja_logistyczna.ipynb
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@ -6370,7 +6370,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
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34
wyk/05_Metody_ewaluacji.ipynb
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@ -307,7 +307,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 24,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -329,7 +329,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 25,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -348,7 +348,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 26,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -420,7 +420,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 27,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -444,7 +444,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 28,
"metadata": {
"slideshow": {
"slide_type": "subslide"
@ -468,7 +468,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 29,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -515,7 +515,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 30,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -543,7 +543,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 31,
"metadata": {
"slideshow": {
"slide_type": "subslide"
@ -573,7 +573,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 32,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -595,7 +595,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 33,
"metadata": {
"slideshow": {
"slide_type": "subslide"
@ -609,7 +609,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 34,
"metadata": {
"slideshow": {
"slide_type": "notes"
@ -629,7 +629,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 35,
"metadata": {
"scrolled": true,
"slideshow": {
@ -640,7 +640,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e622904eeae04709aed0ad3587bd5d7a",
"model_id": "00f3cd62b33841aeb4201c375f7fb8db",
"version_major": 2,
"version_minor": 0
},
@ -657,7 +657,7 @@
"<function __main__.interactive_classification(highlight)>"
]
},
"execution_count": 12,
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
@ -1002,7 +1002,7 @@
},
"source": [
"*$F_\\beta$-measure*:\n",
"$$ F_\\beta = \\frac{(1 + \\beta) \\cdot \\mbox{precision} \\cdot \\mbox{recall}}{\\beta^2 \\cdot \\mbox{precision} + \\mbox{recall}} $$"
"$$ F_\\beta = \\frac{(1 + \\beta^2) \\cdot \\mbox{precision} \\cdot \\mbox{recall}}{\\beta^2 \\cdot \\mbox{precision} + \\mbox{recall}} $$"
]
},
{
@ -1014,7 +1014,7 @@
},
"source": [
"Dla $\\beta = 1$ otrzymujemy:\n",
"$$ F_1 \\, = \\, \\frac{(1 + 1) \\cdot \\mbox{precision} \\cdot \\mbox{recall}}{1^2 \\cdot \\mbox{precision} + \\mbox{recall}} \\, = \\, \\frac{2 \\cdot \\mbox{precision} \\cdot \\mbox{recall}}{\\mbox{precision} + \\mbox{recall}} \\, = \\, F $$"
"$$ F_1 \\, = \\, \\frac{(1 + 1^2) \\cdot \\mbox{precision} \\cdot \\mbox{recall}}{1^2 \\cdot \\mbox{precision} + \\mbox{recall}} \\, = \\, \\frac{2 \\cdot \\mbox{precision} \\cdot \\mbox{recall}}{\\mbox{precision} + \\mbox{recall}} \\, = \\, F $$"
]
},
{
@ -1291,7 +1291,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
"version": "3.10.12"
},
"livereveal": {
"start_slideshow_at": "selected",