Machine-Learning-Examples/Iris.py at master · majidsd/Machine-Learning-Examples · GitHub

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from sklearn.datasets import load_iris
from sklearn import tree
import numpy as np

# work with data, here is iris data for this example
iris = load_iris()
print (iris.feature_names)
print (iris.target_names)

print (iris.data[0])
print (iris.data[1])

print (iris.target[0])
print (iris.target[1])

for i in range(len (iris.target)):
    print ("Example %d: Label %s, features %s" % (i, iris.target[i], iris.data[i]))


test_idx = [0, 50, 100]

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


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

clf = tree.DecisionTreeClassifier()
clf.fit(train_data, train_target)

print (test_target)
print (clf.predict(test_data))