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[SPARK-13257] [Improvement] Refine naive Bayes example by checking model after loading it #11125

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[SPARK-13257] [Improvement] Refine naive Bayes example by checking model after loading it #11125

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Refine naive Bayes example by checking model after loading it
movelikeriver Feb 8, 2016
7e3ea32
fix comments
movelikeriver Feb 12, 2016
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17 changes: 15 additions & 2 deletions examples/src/main/python/mllib/naive_bayes_example.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,9 +17,15 @@

"""
NaiveBayes Example.

Usage:
`spark-submit --master local[4] examples/src/main/python/mllib/naive_bayes_example.py`
"""

from __future__ import print_function

import shutil

from pyspark import SparkContext
# $example on$
from pyspark.mllib.classification import NaiveBayes, NaiveBayesModel
Expand Down Expand Up @@ -50,8 +56,15 @@ def parseLine(line):
# Make prediction and test accuracy.
predictionAndLabel = test.map(lambda p: (model.predict(p.features), p.label))
accuracy = 1.0 * predictionAndLabel.filter(lambda (x, v): x == v).count() / test.count()
print('model accuracy {}'.format(accuracy))

# Save and load model
model.save(sc, "target/tmp/myNaiveBayesModel")
sameModel = NaiveBayesModel.load(sc, "target/tmp/myNaiveBayesModel")
output_dir = 'target/tmp/myNaiveBayesModel'
shutil.rmtree(output_dir, ignore_errors=True)
model.save(sc, output_dir)
sameModel = NaiveBayesModel.load(sc, output_dir)
predictionAndLabel = test.map(lambda p: (sameModel.predict(p.features), p.label))
accuracy = 1.0 * predictionAndLabel.filter(lambda (x, v): x == v).count() / test.count()
print('sameModel accuracy {}'.format(accuracy))

# $example off$