diff options
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala | 11 |
1 files changed, 7 insertions, 4 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala index 0d652aa4c6..6775745167 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala @@ -25,7 +25,8 @@ import org.apache.spark.ml.linalg._ import org.apache.spark.ml.param.{DoubleParam, Param, ParamMap, ParamValidators} import org.apache.spark.ml.param.shared.HasWeightCol import org.apache.spark.ml.util._ -import org.apache.spark.sql.Dataset +import org.apache.spark.mllib.util.MLUtils +import org.apache.spark.sql.{Dataset, Row} import org.apache.spark.sql.functions.{col, lit} import org.apache.spark.sql.types.DoubleType @@ -362,9 +363,11 @@ object NaiveBayesModel extends MLReadable[NaiveBayesModel] { val metadata = DefaultParamsReader.loadMetadata(path, sc, className) val dataPath = new Path(path, "data").toString - val data = sparkSession.read.parquet(dataPath).select("pi", "theta").head() - val pi = data.getAs[Vector](0) - val theta = data.getAs[Matrix](1) + val data = sparkSession.read.parquet(dataPath) + val vecConverted = MLUtils.convertVectorColumnsToML(data, "pi") + val Row(pi: Vector, theta: Matrix) = MLUtils.convertMatrixColumnsToML(vecConverted, "theta") + .select("pi", "theta") + .head() val model = new NaiveBayesModel(metadata.uid, pi, theta) DefaultParamsReader.getAndSetParams(model, metadata) |