diff options
Diffstat (limited to 'examples/src')
-rw-r--r-- | examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala | 2 | ||||
-rw-r--r-- | examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala | 4 |
2 files changed, 3 insertions, 3 deletions
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala index 4811bb70e4..05b7d66f8d 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/LinearRegression.scala @@ -91,7 +91,7 @@ object LinearRegression extends App { Logger.getRootLogger.setLevel(Level.WARN) - val examples = MLUtils.loadLibSVMFile(sc, params.input, multiclass = true).cache() + val examples = MLUtils.loadLibSVMFile(sc, params.input).cache() val splits = examples.randomSplit(Array(0.8, 0.2)) val training = splits(0).cache() diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala index 537e68a099..88acd9dbb0 100644 --- a/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala +++ b/examples/src/main/scala/org/apache/spark/examples/mllib/SparseNaiveBayes.scala @@ -22,7 +22,7 @@ import scopt.OptionParser import org.apache.spark.{SparkConf, SparkContext} import org.apache.spark.mllib.classification.NaiveBayes -import org.apache.spark.mllib.util.{MLUtils, MulticlassLabelParser} +import org.apache.spark.mllib.util.MLUtils /** * An example naive Bayes app. Run with @@ -76,7 +76,7 @@ object SparseNaiveBayes { if (params.minPartitions > 0) params.minPartitions else sc.defaultMinPartitions val examples = - MLUtils.loadLibSVMFile(sc, params.input, multiclass = true, params.numFeatures, minPartitions) + MLUtils.loadLibSVMFile(sc, params.input, params.numFeatures, minPartitions) // Cache examples because it will be used in both training and evaluation. examples.cache() |