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author | Xusen Yin <yinxusen@gmail.com> | 2015-11-10 10:05:53 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-11-10 10:05:53 -0800 |
commit | a81f47ff7498e7063c855ccf75bba81ab101b43e (patch) | |
tree | b5e07052ba1b895da31ce66553355ef171b21efc /examples/src/main/python/mllib | |
parent | 5507a9d0935aa42d65c3a4fa65da680b5af14faf (diff) | |
download | spark-a81f47ff7498e7063c855ccf75bba81ab101b43e.tar.gz spark-a81f47ff7498e7063c855ccf75bba81ab101b43e.tar.bz2 spark-a81f47ff7498e7063c855ccf75bba81ab101b43e.zip |
[SPARK-11382] Replace example code in mllib-decision-tree.md using include_example
https://issues.apache.org/jira/browse/SPARK-11382
B.T.W. I fix an error in naive_bayes_example.py.
Author: Xusen Yin <yinxusen@gmail.com>
Closes #9596 from yinxusen/SPARK-11382.
Diffstat (limited to 'examples/src/main/python/mllib')
3 files changed, 112 insertions, 0 deletions
diff --git a/examples/src/main/python/mllib/decision_tree_classification_example.py b/examples/src/main/python/mllib/decision_tree_classification_example.py new file mode 100644 index 0000000000..1b529768b6 --- /dev/null +++ b/examples/src/main/python/mllib/decision_tree_classification_example.py @@ -0,0 +1,55 @@ +# +# 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. +# + +""" +Decision Tree Classification Example. +""" +from __future__ import print_function + +from pyspark import SparkContext +# $example on$ +from pyspark.mllib.tree import DecisionTree, DecisionTreeModel +from pyspark.mllib.util import MLUtils +# $example off$ + +if __name__ == "__main__": + + sc = SparkContext(appName="PythonDecisionTreeClassificationExample") + + # $example on$ + # Load and parse the data file into an RDD of LabeledPoint. + data = MLUtils.loadLibSVMFile(sc, 'data/mllib/sample_libsvm_data.txt') + # Split the data into training and test sets (30% held out for testing) + (trainingData, testData) = data.randomSplit([0.7, 0.3]) + + # Train a DecisionTree model. + # Empty categoricalFeaturesInfo indicates all features are continuous. + model = DecisionTree.trainClassifier(trainingData, numClasses=2, categoricalFeaturesInfo={}, + impurity='gini', maxDepth=5, maxBins=32) + + # Evaluate model on test instances and compute test error + predictions = model.predict(testData.map(lambda x: x.features)) + labelsAndPredictions = testData.map(lambda lp: lp.label).zip(predictions) + testErr = labelsAndPredictions.filter(lambda (v, p): v != p).count() / float(testData.count()) + print('Test Error = ' + str(testErr)) + print('Learned classification tree model:') + print(model.toDebugString()) + + # Save and load model + model.save(sc, "target/tmp/myDecisionTreeClassificationModel") + sameModel = DecisionTreeModel.load(sc, "target/tmp/myDecisionTreeClassificationModel") + # $example off$ diff --git a/examples/src/main/python/mllib/decision_tree_regression_example.py b/examples/src/main/python/mllib/decision_tree_regression_example.py new file mode 100644 index 0000000000..cf518eac67 --- /dev/null +++ b/examples/src/main/python/mllib/decision_tree_regression_example.py @@ -0,0 +1,56 @@ +# +# 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. +# + +""" +Decision Tree Regression Example. +""" +from __future__ import print_function + +from pyspark import SparkContext +# $example on$ +from pyspark.mllib.tree import DecisionTree, DecisionTreeModel +from pyspark.mllib.util import MLUtils +# $example off$ + +if __name__ == "__main__": + + sc = SparkContext(appName="PythonDecisionTreeRegressionExample") + + # $example on$ + # Load and parse the data file into an RDD of LabeledPoint. + data = MLUtils.loadLibSVMFile(sc, 'data/mllib/sample_libsvm_data.txt') + # Split the data into training and test sets (30% held out for testing) + (trainingData, testData) = data.randomSplit([0.7, 0.3]) + + # Train a DecisionTree model. + # Empty categoricalFeaturesInfo indicates all features are continuous. + model = DecisionTree.trainRegressor(trainingData, categoricalFeaturesInfo={}, + impurity='variance', maxDepth=5, maxBins=32) + + # Evaluate model on test instances and compute test error + predictions = model.predict(testData.map(lambda x: x.features)) + labelsAndPredictions = testData.map(lambda lp: lp.label).zip(predictions) + testMSE = labelsAndPredictions.map(lambda (v, p): (v - p) * (v - p)).sum() /\ + float(testData.count()) + print('Test Mean Squared Error = ' + str(testMSE)) + print('Learned regression tree model:') + print(model.toDebugString()) + + # Save and load model + model.save(sc, "target/tmp/myDecisionTreeRegressionModel") + sameModel = DecisionTreeModel.load(sc, "target/tmp/myDecisionTreeRegressionModel") + # $example off$ diff --git a/examples/src/main/python/mllib/naive_bayes_example.py b/examples/src/main/python/mllib/naive_bayes_example.py index a2e7dacf25..f5e120c678 100644 --- a/examples/src/main/python/mllib/naive_bayes_example.py +++ b/examples/src/main/python/mllib/naive_bayes_example.py @@ -20,6 +20,7 @@ NaiveBayes Example. """ from __future__ import print_function +from pyspark import SparkContext # $example on$ from pyspark.mllib.classification import NaiveBayes, NaiveBayesModel from pyspark.mllib.linalg import Vectors |