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author | Yanbo Liang <ybliang8@gmail.com> | 2015-12-15 16:29:39 -0800 |
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committer | Joseph K. Bradley <joseph@databricks.com> | 2015-12-15 16:29:39 -0800 |
commit | b24c12d7338b47b637698e7458ba90f34cba28c0 (patch) | |
tree | 2e88d1f095ebb49790401947ab611c6ace265fe7 /examples/src/main/java | |
parent | bc1ff9f4a41401599d3a87fb3c23a2078228a29b (diff) | |
download | spark-b24c12d7338b47b637698e7458ba90f34cba28c0.tar.gz spark-b24c12d7338b47b637698e7458ba90f34cba28c0.tar.bz2 spark-b24c12d7338b47b637698e7458ba90f34cba28c0.zip |
[MINOR][ML] Rename weights to coefficients for examples/DeveloperApiExample
Rename ```weights``` to ```coefficients``` for examples/DeveloperApiExample.
cc mengxr jkbradley
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #10280 from yanboliang/spark-coefficients.
Diffstat (limited to 'examples/src/main/java')
-rw-r--r-- | examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java index 0b4c0d9ba9..b9dd3ad957 100644 --- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java +++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java @@ -89,7 +89,7 @@ public class JavaDeveloperApiExample { } if (sumPredictions != 0.0) { throw new Exception("MyJavaLogisticRegression predicted something other than 0," + - " even though all weights are 0!"); + " even though all coefficients are 0!"); } jsc.stop(); @@ -149,12 +149,12 @@ class MyJavaLogisticRegression // Extract columns from data using helper method. JavaRDD<LabeledPoint> oldDataset = extractLabeledPoints(dataset).toJavaRDD(); - // Do learning to estimate the weight vector. + // Do learning to estimate the coefficients vector. int numFeatures = oldDataset.take(1).get(0).features().size(); - Vector weights = Vectors.zeros(numFeatures); // Learning would happen here. + Vector coefficients = Vectors.zeros(numFeatures); // Learning would happen here. // Create a model, and return it. - return new MyJavaLogisticRegressionModel(uid(), weights).setParent(this); + return new MyJavaLogisticRegressionModel(uid(), coefficients).setParent(this); } @Override @@ -173,12 +173,12 @@ class MyJavaLogisticRegression class MyJavaLogisticRegressionModel extends ClassificationModel<Vector, MyJavaLogisticRegressionModel> { - private Vector weights_; - public Vector weights() { return weights_; } + private Vector coefficients_; + public Vector coefficients() { return coefficients_; } - public MyJavaLogisticRegressionModel(String uid, Vector weights) { + public MyJavaLogisticRegressionModel(String uid, Vector coefficients) { this.uid_ = uid; - this.weights_ = weights; + this.coefficients_ = coefficients; } private String uid_ = Identifiable$.MODULE$.randomUID("myJavaLogReg"); @@ -208,7 +208,7 @@ class MyJavaLogisticRegressionModel * modifier. */ public Vector predictRaw(Vector features) { - double margin = BLAS.dot(features, weights_); + double margin = BLAS.dot(features, coefficients_); // There are 2 classes (binary classification), so we return a length-2 vector, // where index i corresponds to class i (i = 0, 1). return Vectors.dense(-margin, margin); @@ -222,7 +222,7 @@ class MyJavaLogisticRegressionModel /** * Number of features the model was trained on. */ - public int numFeatures() { return weights_.size(); } + public int numFeatures() { return coefficients_.size(); } /** * Create a copy of the model. @@ -235,7 +235,7 @@ class MyJavaLogisticRegressionModel */ @Override public MyJavaLogisticRegressionModel copy(ParamMap extra) { - return copyValues(new MyJavaLogisticRegressionModel(uid(), weights_), extra) + return copyValues(new MyJavaLogisticRegressionModel(uid(), coefficients_), extra) .setParent(parent()); } } |