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#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""
Binary Classification Metrics Example.
"""
from __future__ import print_function
import sys
from pyspark import SparkContext, SQLContext
# $example on$
from pyspark.mllib.classification import LogisticRegressionWithLBFGS
from pyspark.mllib.evaluation import BinaryClassificationMetrics
from pyspark.mllib.util import MLUtils
# $example off$
if __name__ == "__main__":
sc = SparkContext(appName="BinaryClassificationMetricsExample")
sqlContext = SQLContext(sc)
# $example on$
# Several of the methods available in scala are currently missing from pyspark
# Load training data in LIBSVM format
data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_binary_classification_data.txt")
# Split data into training (60%) and test (40%)
training, test = data.randomSplit([0.6, 0.4], seed=11L)
training.cache()
# Run training algorithm to build the model
model = LogisticRegressionWithLBFGS.train(training)
# Compute raw scores on the test set
predictionAndLabels = test.map(lambda lp: (float(model.predict(lp.features)), lp.label))
# Instantiate metrics object
metrics = BinaryClassificationMetrics(predictionAndLabels)
# Area under precision-recall curve
print("Area under PR = %s" % metrics.areaUnderPR)
# Area under ROC curve
print("Area under ROC = %s" % metrics.areaUnderROC)
# $example off$
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