- Add the following code fragment into the same Python file:
from sklearn import cross_validationfrom sklearn.naive_bayes import GaussianNBimport numpy as npimport matplotlib.pyplot as pltin_file = 'data_multivar.txt'a = []b = []with open(in_file, 'r') as f: for line in f.readlines(): data = [float(x) for x in line.split(',')] a.append(data[:-1]) b.append(data[-1])a = np.array(a)b = np.array(b)
- Allocate 75% of data for training and 25% of data for testing:
a_training, a_testing, b_training, b_testing = cross_validation.train_test_split(a, b, test_size=0.25, random_state=5)classification_gaussiannb_new = GaussianNB()classification_gaussiannb_new.fit(a_training, b_training)
- Evaluate the classifier performance on test data: ...
