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#!/usr/bin/env python
import feast
import numpy as np
##################################################################
##################################################################
##################################################################
def read_digits(fname='digit.txt'):
'''
read_digits(fname='digit.txt')
read a data file that contains the features and class labels.
each row of the file is a feature vector with the class
label appended.
'''
import csv
fw = csv.reader(open(fname,'rb'), delimiter='\t')
data = []
for line in fw:
data.append( [float(x) for x in line] )
data = np.array(data)
labels = data[:,len(data.transpose())-1]
data = data[:,:len(data.transpose())-1]
return data, labels
##################################################################
##################################################################
##################################################################
print '---> Loading digit data'
data, labels = read_digits('digit.txt')
n_observations = len(data) # number of samples in the data set
n_features = len(data.transpose()) # number of features in the data set
n_select = 15 # how many features to select
method = 'JMI' # feature selection algorithm
print '---> Information'
print ' :n_observations - ' + str(n_observations)
print ' :n_features - ' + str(n_features)
print ' :n_select - ' + str(n_select)
print ' :algorithm - ' + str(method)
selected_features = feast.select(data, labels, n_observations, n_features, n_select, method)
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