scikit-learn Cookbook - Second Edition

Quick SVC – a classifier and regressor

1. Load iris from the datasets module:

import numpy as npimport pandas as pdfrom sklearn import datasetsiris = datasets.load_iris()

2. For simplicity, consider only targets 0 and 1, corresponding to Setosa and Versicolor. Use the Boolean array iris.target < 2 to filter out target 2. Place it within brackets to use it as a filter in defining the observation set X and the target set y:

X = iris.data[iris.target < 2]y = iris.target[iris.target < 2]

3. Now import train_test_split and apply it:

from sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_scoreX_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, random_state= 7)

4. Prepare and run an SVC by importing ...