This topic describes the Covariance component provided by Machine Learning Studio.

In probability theory and statistics, covariance is a measure of the joint variability of two random variables. Variance is a special case of covariance where the two measured variables are the same. If the expected values are E(X) = μ and E(Y) = ν, the covariance between real-number random variables X and Y is calculated by using the following expression: cov(X, Y) = E((X - μ) (Y - ν)).

You can configure the Covariance component by using one of the following methods:
  • Machine Learning Platform for AI (PAI) console
    Tab Parameter Description
    Fields Setting Input Columns The input columns. You can select only BIGINT- or DOUBLE-type columns.
    Tuning Cores The number of cores that you want to use for computing. If you do not specify this parameter, the system automatically allocates the number of cores.
    Memory Size The memory size of each core. If you do not specify this parameter, the system automatically allocates the memory size. Unit: MB.
  • PAI command
    PAI -name cov
        -project algo_public
        -DinputTableName=maple_test_cov_basic12x10_input
        -DoutputTableName=maple_test_cov_basic12x10_output
        -DcoreNum=6
        -DmemSizePerCore=110;
    Parameter Required Description Default value
    inputTableName Yes The name of the input table. No default value
    inputTablePartitions No The partitions that you want to select from the input table for training. Specify this parameter in one of the following formats:
    • Partition_name=value
    • Multi-level partition: name1=value1/name2=value2
    Note If you specify multiple partitions, separate them with commas (,).
    All partitions of the input table
    outputTableName Yes The name of the output table. No default value
    selectedColNames No The columns that you want to select from the input table. All columns
    lifecycle No The lifecycle of the output table. No default value
    coreNum No The number of cores that you want to use for computing. The value of this parameter must be a positive integer. Valid values: 1 to 9999. Automatically allocated
    memSizePerCore No The memory size of each core. Valid values: 1 to 65536. Unit: MB. Automatically allocated