{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "(sup_reg_ex)=\n", "# Example: Supervised Regression App\n", "\n", "To predict a number for a feature contained in the data, use a supervised *regression* method (but not [logistic regression](task1:choosing_topic:logistic)). \n", "\n", "For this example, we'll slightly modify the [previous example](sup_class_ex). Instead of predicting the category *type*, we'll predict the number *sepal-length*. " ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " | sepal-length | \n", "sepal-width | \n", "petal-length | \n", "petal-width | \n", "type | \n", "
---|---|---|---|---|---|
0 | \n", "5.1 | \n", "3.5 | \n", "1.4 | \n", "0.2 | \n", "Iris-setosa | \n", "
1 | \n", "4.9 | \n", "3.0 | \n", "1.4 | \n", "0.2 | \n", "Iris-setosa | \n", "
2 | \n", "4.7 | \n", "3.2 | \n", "1.3 | \n", "0.2 | \n", "Iris-setosa | \n", "
3 | \n", "4.6 | \n", "3.1 | \n", "1.5 | \n", "0.2 | \n", "Iris-setosa | \n", "
4 | \n", "5.0 | \n", "3.6 | \n", "1.4 | \n", "0.2 | \n", "Iris-setosa | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
145 | \n", "6.7 | \n", "3.0 | \n", "5.2 | \n", "2.3 | \n", "Iris-virginica | \n", "
146 | \n", "6.3 | \n", "2.5 | \n", "5.0 | \n", "1.9 | \n", "Iris-virginica | \n", "
147 | \n", "6.5 | \n", "3.0 | \n", "5.2 | \n", "2.0 | \n", "Iris-virginica | \n", "
148 | \n", "6.2 | \n", "3.4 | \n", "5.4 | \n", "2.3 | \n", "Iris-virginica | \n", "
149 | \n", "5.9 | \n", "3.0 | \n", "5.1 | \n", "1.8 | \n", "Iris-virginica | \n", "