{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "OJFRKa5M41ok" }, "source": [ "# El problema\n", "\n", "Vamos a utilizar para ello el IRIS DataSet pero considerando únicamente dos características (nos facilitará la visualización de los resultados)\n", "\n", "## Iris DataSet\n", "\n", "\n", "\n", "Esta es quizás la base de datos más conocida en el mundo del análisis de datos. El conjunto de datos contiene 3 clases de 50 casos cada una, donde cada clase se refiere a un tipo de planta de iris. Una de las clases es linealmente separable de las otras 2; estas últimas NO son linealmente separables entre sí.\n", "\n", "Objetivo: clase de planta de iris.\n", "\n", "\n", "# 0. Carga de Datos\n", "\n", "En este caso los datos nos la facilita la propia API de scikit-learn\n", "\n" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "id": "pp9tjdSA6rR5" }, "outputs": [], "source": [ "# import some data to play with\n", "from sklearn import datasets\n", "iris = datasets.load_iris()\n", "\n", "# we only take the first two features.\n", "# We could avoid this ugly # slicing by using a two-dim dataset\n", "X = iris.data\n", "y = iris.target\n" ] }, { "cell_type": "markdown", "metadata": { "id": "8tye7Kut6vPB" }, "source": [ "Posteriomente lo cargamos en un DataFrame de Pandas con el nombre de *df_iris*" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "id": "rxVQ7L5c4B-x", "outputId": "c4cf5183-eefc-4b4c-d2bd-9e5c5c3d91fc" }, "outputs": [ { "data": { "text/html": [ "
\n", " | sepal length (cm) | \n", "sepal width (cm) | \n", "petal length (cm) | \n", "petal width (cm) | \n", "target | \n", "
---|---|---|---|---|---|
0 | \n", "5.1 | \n", "3.5 | \n", "1.4 | \n", "0.2 | \n", "0 | \n", "
1 | \n", "4.9 | \n", "3.0 | \n", "1.4 | \n", "0.2 | \n", "0 | \n", "
2 | \n", "4.7 | \n", "3.2 | \n", "1.3 | \n", "0.2 | \n", "0 | \n", "
3 | \n", "4.6 | \n", "3.1 | \n", "1.5 | \n", "0.2 | \n", "0 | \n", "
4 | \n", "5.0 | \n", "3.6 | \n", "1.4 | \n", "0.2 | \n", "0 | \n", "