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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "bPLQQB5PbvPX"
+ },
+ "source": [
+ "# Лабораторная работа 1 (Регрессионный анализ)\n",
+ "\n",
+ "ФИО |Вариант |Никнейм\n",
+ "---------------------|---------|----------\n",
+ "Елистратова П. А. | 6 | TIoJIuHa\n",
+ "\n",
+ "**Цель:** научится применять модели линейной регрессии библиотеки scikit-learn к набору эмпирических данных\n",
+ "\n",
+ "**Дано:** сsv-файл\n",
+ "\n",
+ "**Результат:** эмпирическая формула\n",
+ "\n",
+ "**Ход выполнения:** \n",
+ "1. Загрузить данные из файла.\n",
+ "2. Визуализировать загруженные данные (диаграмма рассеяния, график).\n",
+ "3. Разбить данные на обучающую и тестовую выборки.\n",
+ "4. Выбрать модель регрессии.\n",
+ "5. Обучить модель регрессии на обучающих данных.\n",
+ "6. Проверить качество полученной модели на тестовых данных.\n",
+ "7. Визуализировать результат.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "b15Hd86NrGgy"
+ },
+ "source": [
+ "## Загрузка датасета"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "mu7Um4QBbzqr",
+ "outputId": "1b90e777-cec0-4722-a5de-31ec5a419a73"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting scikit-learn\n",
+ " Obtaining dependency information for scikit-learn from https://files.pythonhosted.org/packages/01/18/d154dc1638803adf987910cdd07097d9c526663a55666a97c124d09fb96a/scikit_learn-1.8.0-cp311-cp311-macosx_12_0_arm64.whl.metadata\n",
+ " Downloading scikit_learn-1.8.0-cp311-cp311-macosx_12_0_arm64.whl.metadata (11 kB)\n",
+ "Requirement already satisfied: numpy>=1.24.1 in /Users/p.elistratova/dev/studies/ml/venv/lib/python3.11/site-packages (from scikit-learn) (2.3.5)\n",
+ "Collecting scipy>=1.10.0 (from scikit-learn)\n",
+ " Obtaining dependency information for scipy>=1.10.0 from https://files.pythonhosted.org/packages/7c/89/d70e9f628749b7e4db2aa4cd89735502ff3f08f7b9b27d2e799485987cd9/scipy-1.16.3-cp311-cp311-macosx_12_0_arm64.whl.metadata\n",
+ " Downloading scipy-1.16.3-cp311-cp311-macosx_12_0_arm64.whl.metadata (62 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.0/62.0 kB\u001b[0m \u001b[31m730.2 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m0:01\u001b[0m\n",
+ "\u001b[?25hCollecting joblib>=1.3.0 (from scikit-learn)\n",
+ " Obtaining dependency information for joblib>=1.3.0 from https://files.pythonhosted.org/packages/1e/e8/685f47e0d754320684db4425a0967f7d3fa70126bffd76110b7009a0090f/joblib-1.5.2-py3-none-any.whl.metadata\n",
+ " Downloading joblib-1.5.2-py3-none-any.whl.metadata (5.6 kB)\n",
+ "Collecting threadpoolctl>=3.2.0 (from scikit-learn)\n",
+ " Obtaining dependency information for threadpoolctl>=3.2.0 from https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl.metadata\n",
+ " Using cached threadpoolctl-3.6.0-py3-none-any.whl.metadata (13 kB)\n",
+ "Downloading scikit_learn-1.8.0-cp311-cp311-macosx_12_0_arm64.whl (8.1 MB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.1/8.1 MB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
+ "\u001b[?25hDownloading joblib-1.5.2-py3-none-any.whl (308 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m308.4/308.4 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
+ "\u001b[?25hDownloading scipy-1.16.3-cp311-cp311-macosx_12_0_arm64.whl (28.9 MB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m28.9/28.9 MB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
+ "\u001b[?25hUsing cached threadpoolctl-3.6.0-py3-none-any.whl (18 kB)\n",
+ "Installing collected packages: threadpoolctl, scipy, joblib, scikit-learn\n",
+ "Successfully installed joblib-1.5.2 scikit-learn-1.8.0 scipy-1.16.3 threadpoolctl-3.6.0\n",
+ "\n",
+ "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.3\u001b[0m\n",
+ "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install scikit-learn"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 359
+ },
+ "id": "ElWEH1CiJa29",
+ "outputId": "4ee32df8-ebdc-49d6-cfc6-d5a987bb5efa"
+ },
+ "outputs": [
+ {
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