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author | Yuhao Yang <hhbyyh@gmail.com> | 2016-04-13 13:58:35 -0700 |
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committer | Joseph K. Bradley <joseph@databricks.com> | 2016-04-13 13:58:35 -0700 |
commit | 781df499836e4216939e0febdcd5f89d30645759 (patch) | |
tree | f27ffcec85b7e7661eeefd6b02b2e8aa8df01cf5 /examples/src/main/java | |
parent | fcdd69260ec75c180f4d727ff2625ca9bf0bdad7 (diff) | |
download | spark-781df499836e4216939e0febdcd5f89d30645759.tar.gz spark-781df499836e4216939e0febdcd5f89d30645759.tar.bz2 spark-781df499836e4216939e0febdcd5f89d30645759.zip |
[SPARK-13089][ML] [Doc] spark.ml Naive Bayes user guide and examples
jira: https://issues.apache.org/jira/browse/SPARK-13089
Add section in ml-classification.md for NaiveBayes DataFrame-based API, plus example code (using include_example to clip code from examples/ folder files).
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #11015 from hhbyyh/naiveBayesDoc.
Diffstat (limited to 'examples/src/main/java')
-rw-r--r-- | examples/src/main/java/org/apache/spark/examples/ml/JavaNaiveBayesExample.java | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaNaiveBayesExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaNaiveBayesExample.java new file mode 100644 index 0000000000..41d7ad75b9 --- /dev/null +++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaNaiveBayesExample.java @@ -0,0 +1,64 @@ +/* + * 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. + */ + +package org.apache.spark.examples.ml; + + +import org.apache.spark.SparkConf; +import org.apache.spark.api.java.JavaSparkContext; +// $example on$ +import org.apache.spark.ml.classification.NaiveBayes; +import org.apache.spark.ml.classification.NaiveBayesModel; +import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator; +import org.apache.spark.sql.Dataset; +import org.apache.spark.sql.Row; +import org.apache.spark.sql.SQLContext; +// $example off$ + +/** + * An example for Naive Bayes Classification. + */ +public class JavaNaiveBayesExample { + + public static void main(String[] args) { + SparkConf conf = new SparkConf().setAppName("JavaNaiveBayesExample"); + JavaSparkContext jsc = new JavaSparkContext(conf); + SQLContext jsql = new SQLContext(jsc); + + // $example on$ + // Load training data + Dataset<Row> dataFrame = jsql.read().format("libsvm").load("data/mllib/sample_libsvm_data.txt"); + // Split the data into train and test + Dataset<Row>[] splits = dataFrame.randomSplit(new double[]{0.6, 0.4}, 1234L); + Dataset<Row> train = splits[0]; + Dataset<Row> test = splits[1]; + + // create the trainer and set its parameters + NaiveBayes nb = new NaiveBayes(); + // train the model + NaiveBayesModel model = nb.fit(train); + // compute precision on the test set + Dataset<Row> result = model.transform(test); + Dataset<Row> predictionAndLabels = result.select("prediction", "label"); + MulticlassClassificationEvaluator evaluator = new MulticlassClassificationEvaluator() + .setMetricName("precision"); + System.out.println("Precision = " + evaluator.evaluate(predictionAndLabels)); + // $example off$ + + jsc.stop(); + } +} |