{
"cells": [
{
"cell_type": "markdown",
"id": "95ad8a4c",
"metadata": {},
"source": [
"# Lesson 26: multilayer perceptron demonstration\n",
"\n",
"## Notebook set up\n",
"### Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "5b95b6b1",
"metadata": {},
"outputs": [],
"source": [
"# Third party imports\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.neural_network import MLPRegressor\n",
"from sklearn.preprocessing import StandardScaler"
]
},
{
"cell_type": "markdown",
"id": "14d2230f",
"metadata": {},
"source": [
"## 1. Data preparation\n",
"\n",
"### 1.1. Load California housing data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e5eb80ea",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" MedInc | \n",
" HouseAge | \n",
" AveRooms | \n",
" AveBedrms | \n",
" Population | \n",
" AveOccup | \n",
" Latitude | \n",
" Longitude | \n",
" MedHouseVal | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 8.3252 | \n",
" 41.0 | \n",
" 6.984127 | \n",
" 1.023810 | \n",
" 322.0 | \n",
" 2.555556 | \n",
" 37.88 | \n",
" -122.23 | \n",
" 4.526 | \n",
"
\n",
" \n",
" | 1 | \n",
" 8.3014 | \n",
" 21.0 | \n",
" 6.238137 | \n",
" 0.971880 | \n",
" 2401.0 | \n",
" 2.109842 | \n",
" 37.86 | \n",
" -122.22 | \n",
" 3.585 | \n",
"
\n",
" \n",
" | 2 | \n",
" 7.2574 | \n",
" 52.0 | \n",
" 8.288136 | \n",
" 1.073446 | \n",
" 496.0 | \n",
" 2.802260 | \n",
" 37.85 | \n",
" -122.24 | \n",
" 3.521 | \n",
"
\n",
" \n",
" | 3 | \n",
" 5.6431 | \n",
" 52.0 | \n",
" 5.817352 | \n",
" 1.073059 | \n",
" 558.0 | \n",
" 2.547945 | \n",
" 37.85 | \n",
" -122.25 | \n",
" 3.413 | \n",
"
\n",
" \n",
" | 4 | \n",
" 3.8462 | \n",
" 52.0 | \n",
" 6.281853 | \n",
" 1.081081 | \n",
" 565.0 | \n",
" 2.181467 | \n",
" 37.85 | \n",
" -122.25 | \n",
" 3.422 | \n",
"
\n",
" \n",
"
\n",
"