Package

org.apache.spark.ml.source

libsvm

Permalink

package libsvm

Visibility
  1. Public
  2. All

Type Members

  1. class DefaultSource extends FileFormat with DataSourceRegister

    Permalink

    libsvm package implements Spark SQL data source API for loading LIBSVM data as DataFrame.

    libsvm package implements Spark SQL data source API for loading LIBSVM data as DataFrame. The loaded DataFrame has two columns: label containing labels stored as doubles and features containing feature vectors stored as Vectors.

    To use LIBSVM data source, you need to set "libsvm" as the format in DataFrameReader and optionally specify options, for example:

    // Scala
    val df = spark.read.format("libsvm")
      .option("numFeatures", "780")
      .load("data/mllib/sample_libsvm_data.txt")
    
    // Java
    DataFrame df = spark.read().format("libsvm")
      .option("numFeatures, "780")
      .load("data/mllib/sample_libsvm_data.txt");

    LIBSVM data source supports the following options:

    • "numFeatures": number of features. If unspecified or nonpositive, the number of features will be determined automatically at the cost of one additional pass. This is also useful when the dataset is already split into multiple files and you want to load them separately, because some features may not present in certain files, which leads to inconsistent feature dimensions.
    • "vectorType": feature vector type, "sparse" (default) or "dense".
    Annotations
    @Since( "1.6.0" )
    See also

    LIBSVM datasets

Members