Solving classical Iris problem using machine learning.

ml2.py

#!/usr/bin/env python
import numpy as np

from sklearn import tree
from sklearn.datasets import load_iris

iris = load_iris()
test_tdx = [0, 50, 100]

# training data
train_target = np.delete(iris.target, test_tdx)
train_data = np.delete(iris.data, test_tdx, axis=0)

# testing data
test_data = iris.data[test_tdx]
test_target = iris.target[test_tdx]

clf = tree.DecisionTreeClassifier()
clf = clf.fit(train_data, train_target)
print test_target
print clf.predict(test_data)