Beginners guide to their first machine learning program.

01-First_Program.py

'''
The program predicts if a fruit is an apple or an orange from examining a
given data set of four fruits with two labels - apple or orange.
'''


import sklearn # Import SciKit Learn
from sklearn import tree # Import a classifier called 'DescisionTreeClassifier'

# Dataset of 4 fruits with 2 labels, apple and orange

'''
Feeding data in form [x, y] where, 
x is weight of fruit in grams and, y is texture of the fruit - smooth or bumpy.
0 for smooth and 1 for bumpy. 
'''

features = [[140, 0], [130, 0], [150, 1], [145, 1]] # Feeding features of the data in 'features'
labels = ['apple','apple','orange','orange']  # Feeding output labels of the data in 'labels'

classifier = tree.DecisionTreeClassifier() # Initializing the tree classifier
classifier.fit(features, labels) # Feeding the data to the classifier

# Ask your program to evaluate a fruit from the given data.

print(classifier.predict([[147, 1]])) # Predicting a New Fruit of 147 grams and bumpy texture.