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-rw-r--r--mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java4
-rw-r--r--mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala6
2 files changed, 5 insertions, 5 deletions
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java
index 09a9fba0c1..a700c9cddb 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java
@@ -68,7 +68,7 @@ public class JavaNaiveBayesSuite implements Serializable {
assert(nb.getLabelCol() == "label");
assert(nb.getFeaturesCol() == "features");
assert(nb.getPredictionCol() == "prediction");
- assert(nb.getLambda() == 1.0);
+ assert(nb.getSmoothing() == 1.0);
assert(nb.getModelType() == "multinomial");
}
@@ -89,7 +89,7 @@ public class JavaNaiveBayesSuite implements Serializable {
});
DataFrame dataset = jsql.createDataFrame(jrdd, schema);
- NaiveBayes nb = new NaiveBayes().setLambda(0.5).setModelType("multinomial");
+ NaiveBayes nb = new NaiveBayes().setSmoothing(0.5).setModelType("multinomial");
NaiveBayesModel model = nb.fit(dataset);
DataFrame predictionAndLabels = model.transform(dataset).select("prediction", "label");
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
index 76381a2741..264bde3703 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
@@ -58,7 +58,7 @@ class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext {
assert(nb.getLabelCol === "label")
assert(nb.getFeaturesCol === "features")
assert(nb.getPredictionCol === "prediction")
- assert(nb.getLambda === 1.0)
+ assert(nb.getSmoothing === 1.0)
assert(nb.getModelType === "multinomial")
}
@@ -75,7 +75,7 @@ class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext {
val testDataset = sqlContext.createDataFrame(generateNaiveBayesInput(
piArray, thetaArray, nPoints, 42, "multinomial"))
- val nb = new NaiveBayes().setLambda(1.0).setModelType("multinomial")
+ val nb = new NaiveBayes().setSmoothing(1.0).setModelType("multinomial")
val model = nb.fit(testDataset)
validateModelFit(pi, theta, model)
@@ -101,7 +101,7 @@ class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext {
val testDataset = sqlContext.createDataFrame(generateNaiveBayesInput(
piArray, thetaArray, nPoints, 45, "bernoulli"))
- val nb = new NaiveBayes().setLambda(1.0).setModelType("bernoulli")
+ val nb = new NaiveBayes().setSmoothing(1.0).setModelType("bernoulli")
val model = nb.fit(testDataset)
validateModelFit(pi, theta, model)