Repository: spark Updated Branches: refs/heads/master bc1ff9f4a -> b24c12d73
[MINOR][ML] Rename weights to coefficients for examples/DeveloperApiExample Rename ```weights``` to ```coefficients``` for examples/DeveloperApiExample. cc mengxr jkbradley Author: Yanbo Liang <yblia...@gmail.com> Closes #10280 from yanboliang/spark-coefficients. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/b24c12d7 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/b24c12d7 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/b24c12d7 Branch: refs/heads/master Commit: b24c12d7338b47b637698e7458ba90f34cba28c0 Parents: bc1ff9f Author: Yanbo Liang <yblia...@gmail.com> Authored: Tue Dec 15 16:29:39 2015 -0800 Committer: Joseph K. Bradley <jos...@databricks.com> Committed: Tue Dec 15 16:29:39 2015 -0800 ---------------------------------------------------------------------- .../examples/ml/JavaDeveloperApiExample.java | 22 ++++++++++---------- .../spark/examples/ml/DeveloperApiExample.scala | 16 +++++++------- 2 files changed, 19 insertions(+), 19 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/b24c12d7/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java ---------------------------------------------------------------------- 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 0b4c0d9..b9dd3ad 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()); } } http://git-wip-us.apache.org/repos/asf/spark/blob/b24c12d7/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala ---------------------------------------------------------------------- diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala index 3758edc..c1f63c6 100644 --- a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala +++ b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala @@ -75,7 +75,7 @@ object DeveloperApiExample { prediction }.sum assert(sumPredictions == 0.0, - "MyLogisticRegression predicted something other than 0, even though all weights are 0!") + "MyLogisticRegression predicted something other than 0, even though all coefficients are 0!") sc.stop() } @@ -124,12 +124,12 @@ private class MyLogisticRegression(override val uid: String) // Extract columns from data using helper method. val oldDataset = extractLabeledPoints(dataset) - // Do learning to estimate the weight vector. + // Do learning to estimate the coefficients vector. val numFeatures = oldDataset.take(1)(0).features.size - val weights = Vectors.zeros(numFeatures) // Learning would happen here. + val coefficients = Vectors.zeros(numFeatures) // Learning would happen here. // Create a model, and return it. - new MyLogisticRegressionModel(uid, weights).setParent(this) + new MyLogisticRegressionModel(uid, coefficients).setParent(this) } override def copy(extra: ParamMap): MyLogisticRegression = defaultCopy(extra) @@ -142,7 +142,7 @@ private class MyLogisticRegression(override val uid: String) */ private class MyLogisticRegressionModel( override val uid: String, - val weights: Vector) + val coefficients: Vector) extends ClassificationModel[Vector, MyLogisticRegressionModel] with MyLogisticRegressionParams { @@ -163,7 +163,7 @@ private class MyLogisticRegressionModel( * confidence for that label. */ override protected def predictRaw(features: Vector): Vector = { - val margin = BLAS.dot(features, weights) + val 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). Vectors.dense(-margin, margin) @@ -173,7 +173,7 @@ private class MyLogisticRegressionModel( override val numClasses: Int = 2 /** Number of features the model was trained on. */ - override val numFeatures: Int = weights.size + override val numFeatures: Int = coefficients.size /** * Create a copy of the model. @@ -182,7 +182,7 @@ private class MyLogisticRegressionModel( * This is used for the default implementation of [[transform()]]. */ override def copy(extra: ParamMap): MyLogisticRegressionModel = { - copyValues(new MyLogisticRegressionModel(uid, weights), extra).setParent(parent) + copyValues(new MyLogisticRegressionModel(uid, coefficients), extra).setParent(parent) } } // scalastyle:on println --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org