diff --git a/docs/learning.ipynb b/docs/learning.ipynb index 1fbd782..6cf0467 100644 --- a/docs/learning.ipynb +++ b/docs/learning.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 12, + "execution_count": 31, "id": "faafb9a0", "metadata": {}, "outputs": [ @@ -110,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 32, "id": "8342340f", "metadata": {}, "outputs": [], @@ -135,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 33, "id": "9dfdc01f", "metadata": {}, "outputs": [], @@ -184,7 +184,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 34, "id": "99de3ed7", "metadata": {}, "outputs": [ @@ -217,7 +217,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 35, "id": "09eca16d", "metadata": {}, "outputs": [ @@ -255,7 +255,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 36, "id": "b94a89f2", "metadata": {}, "outputs": [ @@ -332,7 +332,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 37, "id": "4f1c169f", "metadata": {}, "outputs": [ @@ -369,7 +369,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 38, "id": "91cedffb", "metadata": {}, "outputs": [ @@ -466,7 +466,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 39, "id": "4c21cd56", "metadata": {}, "outputs": [ @@ -482,9 +482,9 @@ "text/markdown": [ "| Méthode | R² |\n", "| :---: | :---: |\n", - "|AD|0.386319|\n", - "|Normalisation + AD|0.386319|\n", - "|Standardisation + AD|0.386319|\n" + "|AD|0.483688|\n", + "|Normalisation + AD|0.483688|\n", + "|Standardisation + AD|0.483719|\n" ], "text/plain": [ "" @@ -505,9 +505,9 @@ "text/markdown": [ "| Méthode | R² |\n", "| :---: | :---: |\n", - "|AD|0.382689|\n", - "|Normalisation + AD|0.382695|\n", - "|Standardisation + AD|0.382691|\n" + "|AD|0.501187|\n", + "|Normalisation + AD|0.501187|\n", + "|Standardisation + AD|0.501185|\n" ], "text/plain": [ "" @@ -528,9 +528,9 @@ "text/markdown": [ "| Méthode | R² |\n", "| :---: | :---: |\n", - "|AD|0.371764|\n", - "|Normalisation + AD|0.374744|\n", - "|Standardisation + AD|0.371729|\n" + "|AD|0.511089|\n", + "|Normalisation + AD|0.508518|\n", + "|Standardisation + AD|0.512649|\n" ], "text/plain": [ "" @@ -543,7 +543,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "best score= 0.3863187373819251 depth= 3 method= AD\n" + "best score= 0.512649496806262 depth= 5 method= Standardisation + AD\n" ] } ], @@ -571,7 +571,7 @@ " else make_pipeline(scaler(), DecisionTreeRegressor(max_depth=depth))\n", " )\n", " model.fit(X_train, y_train)\n", - " score: float = cross_val_score(model, X_test, y_test, cv=5).mean()\n", + " score: float = cross_val_score(model, X_train, y_train, cv=5).mean()\n", " ad_table.ajoutligne(f\"{name}\", score)\n", "\n", " if score > best_score_ad:\n", @@ -625,7 +625,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 40, "id": "f72f499f", "metadata": {}, "outputs": [ @@ -641,9 +641,9 @@ "text/markdown": [ "| Méthode | R² |\n", "| :---: | :---: |\n", - "|KNN|0.370389|\n", - "|Normalisation + KNN|0.341947|\n", - "|Standardisation + KNN|0.369662|\n" + "|KNN|0.485764|\n", + "|Normalisation + KNN|0.497729|\n", + "|Standardisation + KNN|0.489906|\n" ], "text/plain": [ "" @@ -664,9 +664,9 @@ "text/markdown": [ "| Méthode | R² |\n", "| :---: | :---: |\n", - "|KNN|0.390801|\n", - "|Normalisation + KNN|0.349482|\n", - "|Standardisation + KNN|0.381631|\n" + "|KNN|0.504888|\n", + "|Normalisation + KNN|0.500504|\n", + "|Standardisation + KNN|0.493475|\n" ], "text/plain": [ "" @@ -679,7 +679,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "best score= 0.39080066451618123 neighbor= 5 method= KNN\n" + "best score= 0.5048884037669835 neighbor= 5 method= KNN\n" ] } ], @@ -707,10 +707,10 @@ " else make_pipeline(scaler(), KNeighborsRegressor(n_neighbors=n))\n", " )\n", " model.fit(X_train, y_train)\n", - " score: float = cross_val_score(model, X_test, y_test, cv=5).mean()\n", + " score: float = cross_val_score(model, X_train, y_train, cv=5).mean()\n", " knn_table.ajoutligne(f\"{name}\", score)\n", "\n", - " if score > best_score_ad:\n", + " if score > best_score_knn:\n", " best_score_knn = score\n", " best_neighbor = n\n", " best_scaler_name = name\n", @@ -749,7 +749,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 41, "id": "9f764f3a", "metadata": {}, "outputs": [ @@ -759,8 +759,8 @@ "| Méthode | R² |\n", "| :---: | :---: |\n", "|LR|0.452908|\n", - "|AD|0.386319|\n", - "|KNN|0.390801|\n" + "|AD|0.512649|\n", + "|KNN|0.504888|\n" ], "text/plain": [ "" @@ -773,7 +773,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "best_model= LR best_scaler= MinMaxScaler\n" + "best_model= AD best_scaler= StandardScaler\n" ] } ], @@ -813,7 +813,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 42, "id": "9084e87e", "metadata": {}, "outputs": [ @@ -850,17 +850,17 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 43, "id": "fdcdfb17", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.24194691318111572" + "0.3938363073944231" ] }, - "execution_count": 24, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } @@ -902,7 +902,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 44, "id": "c4f6c27f", "metadata": {}, "outputs": [ @@ -912,7 +912,7 @@ "" ] }, - "execution_count": 25, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" }, @@ -947,7 +947,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 45, "id": "2e512052", "metadata": {}, "outputs": [ @@ -1134,7 +1134,7 @@ "App_Haut-Médoc -0.070383" ] }, - "execution_count": 26, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } @@ -1155,17 +1155,17 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 46, "id": "4010aa12", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.24551258031003886" + "0.4489472637581393" ] }, - "execution_count": 27, + "execution_count": 46, "metadata": {}, "output_type": "execute_result" } @@ -1213,7 +1213,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 47, "id": "1510f763", "metadata": {}, "outputs": [ @@ -1222,9 +1222,9 @@ "text/markdown": [ "| Méthode | R² |\n", "| :---: | :---: |\n", - "|Random Forest|0.492498|\n", - "|Normalisation + RF|0.492721|\n", - "|Standardisation + RF|0.500235|\n" + "|Random Forest|0.496806|\n", + "|Normalisation + RF|0.494283|\n", + "|Standardisation + RF|0.486890|\n" ], "text/plain": [ ""