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#!/usr/bin/env python
import csv
from sklearn import svm
import numpy as np
import scipy.sparse as sp
import sys
from sklearn.externals import joblib
from mlloutils import expand_to_vectors
if len(sys.argv) < 2:
print >> sys.stderr, 'Usage: python '+sys.argv[0]+' <test csv input> <persistent model input>'
exit(0)
model_name = sys.argv[2]
print >> sys.stderr, 'Loading classifier from '+model_name
clf = joblib.load(model_name)
test_name = sys.argv[1]
print >> sys.stderr, 'Loading test set from '+test_name
test_vectors, ids = expand_to_vectors(test_name, 1, 2, [6, 7, 8], 0, False)
print "%d vectors with dimension %d" % test_vectors.shape
print >> sys.stderr, 'Predicting...'
prediction_matrix = clf.predict(test_vectors)
prediction = prediction_matrix.tolist()
print 'id,good'
for index, value in enumerate(ids):
print str(value)+','+str(prediction[index])
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