diff options
Diffstat (limited to 'examples/src/main/python/mllib/isotonic_regression_example.py')
| -rw-r--r-- | examples/src/main/python/mllib/isotonic_regression_example.py | 11 |
1 files changed, 8 insertions, 3 deletions
diff --git a/examples/src/main/python/mllib/isotonic_regression_example.py b/examples/src/main/python/mllib/isotonic_regression_example.py index 89dc9f4b66..33d618ab48 100644 --- a/examples/src/main/python/mllib/isotonic_regression_example.py +++ b/examples/src/main/python/mllib/isotonic_regression_example.py @@ -23,7 +23,8 @@ from __future__ import print_function from pyspark import SparkContext # $example on$ import math -from pyspark.mllib.regression import IsotonicRegression, IsotonicRegressionModel +from pyspark.mllib.regression import LabeledPoint, IsotonicRegression, IsotonicRegressionModel +from pyspark.mllib.util import MLUtils # $example off$ if __name__ == "__main__": @@ -31,10 +32,14 @@ if __name__ == "__main__": sc = SparkContext(appName="PythonIsotonicRegressionExample") # $example on$ - data = sc.textFile("data/mllib/sample_isotonic_regression_data.txt") + # Load and parse the data + def parsePoint(labeledData): + return (labeledData.label, labeledData.features[0], 1.0) + + data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_isotonic_regression_libsvm_data.txt") # Create label, feature, weight tuples from input data with weight set to default value 1.0. - parsedData = data.map(lambda line: tuple([float(x) for x in line.split(',')]) + (1.0,)) + parsedData = data.map(parsePoint) # Split data into training (60%) and test (40%) sets. training, test = parsedData.randomSplit([0.6, 0.4], 11) |