Machine Learning for OpenCV

Loading the training data

The Iris dataset is included with scikit-learn. We first load all the necessary modules, as we did in our earlier examples:

In [1]: import numpy as np...     import cv2...     from sklearn import datasets...     from sklearn import model_selection...     from sklearn import metrics...     import matplotlib.pyplot as plt...     %matplotlib inlineIn [2]: plt.style.use('ggplot')

Then, loading the dataset is a one-liner:

In [3]: iris = datasets.load_iris()

This function returns a dictionary we call iris, which contains a bunch of different fields:

In [4]: dir(iris)Out[4]: ['DESCR', 'data', 'feature_names', 'target', 'target_names']

Here, all the data points are contained in 'data'. There are 150 data points, each of which have four feature ...