This topic describes the Correlation Coefficient Matrix component provided by Machine Learning Studio.

The correlation coefficient indicates the correlation between columns in a matrix. The coefficient is in the range of [-1,1]. The count parameter is measured when the value is the number of non-zero elements in two consecutive columns.

Configure the component

You can configure the component by using one of the following methods:
  • Machine Learning Platform for AI console
    Tab Parameter Description
    Fields Setting All Selected by Default N/A
    Tuning Cores This parameter is used with Memory Size.
    Memory Size This parameter is used with Cores.
  • PAI command
    PAI -name corrcoef
        -project algo_public
        -DinputTableName=maple_test_corrcoef_basic12x10_input
        -DoutputTableName=maple_test_corrcoef_basic12x10_output
        -DcoreNum=1
        -DmemSizePerCore=110;
    Parameter Required Description Default value
    inputTableName Yes The name of the input table. No default value
    inputTablePartitions No The partitions selected from the input table for training. The system supports the following formats:
    • Partition_name=value
    • name1=value1/name2=value2: multi-level partitions
    Note If you specify multiple partitions, separate them with commas (,).
    No default value
    outputTableName Yes The names of output tables. No default value
    selectedColNames No The columns selected from the input table. All columns are selected by default.
    lifecycle No The lifecycle of the output table. No default value
    coreNum No This parameter is used with memSizePerCore. The value must be a positive integer. Valid values: [1, 9999]. Automatically calculated
    memSizePerCore No The memory size of each core. Unit: MB. A positive integer in the range of [1024, 64 × 1024] Automatically calculated

Example

  • Input
    col0:double col1:bigint col2:double col3:bigint col4:double col5:bigint col6:double col7:bigint col8:double col9:double
    19 95 33 52 115 43 32 98 76 40
    114 26 101 69 56 59 116 23 109 105
    103 89 7 9 65 118 73 50 55 81
    79 20 63 71 5 24 77 31 21 75
    87 16 66 47 25 14 42 99 108 57
    11 104 38 37 106 51 3 91 80 97
    84 30 70 46 8 6 94 22 45 48
    35 17 107 64 10 112 53 34 90 96
    13 61 39 1 29 117 112 2 82 28
    62 4 102 88 100 36 67 54 12 85
    49 27 44 93 68 110 60 72 86 58
    92 119 0 113 41 15 74 83 18 111
  • PAI command
    PAI -name corrcoef
        -project algo_public
        -DinputTableName=maple_test_corrcoef_basic12x10_input
        -DoutputTableName=maple_test_corrcoef_basic12x10_output
        -DcoreNum=1
        -DmemSizePerCore=110;
  • Output
    columnsnames col0 col1 col2 col3 col4 col5 col6 col7 col8 col9
    col0 1 -0.2115657251820724 0.0598306259706561 0.2599903570684693 -0.3483249188225586 -0.28716254396809926 0.47880162127435116 -0.13646519484213326 -0.19500158764680092 0.3897390240949085
    col1 -0.2115657251820724 1 -0.8444477377898585 -0.17507636221594533 0.40943384150571377 0.09135976026101403 -0.3018506374626574 0.40733726912808044 -0.11827739124590071 0.12433851389455183
    col2 0.0598306259706561 -0.8444477377898585 1 0.18518346647293102 -0.20934839228057014 -0.1896417512389659 0.1799377498863213 -0.3858885676469948 0.20254569203773892 0.13476160753756655
    col3 0.2599903570684693 -0.17507636221594533 0.18518346647293102 1 0.03988018649854009 -0.43737887418329147 -0.053818296425267184 0.2900856441586986 -0.3607547910075688 0.4912019074930449
    col4 -0.3483249188225586 0.40943384150571377 -0.20934839228057014 0.03988018649854009 1 0.1465605209246875 -0.5016030364347955 0.5496024325711117 0.013743256115394122 0.07497231559184887
    col5 -0.28716254396809926 0.09135976026101403 -0.1896417512389659 -0.43737887418329147 0.1465605209246875 1 0.16729809310873522 -0.29890655828796964 0.3618518101014617 -0.1713960957286885
    col6 0.47880162127435116 -0.3018506374626574 0.1799377498863213 -0.053818296425267184 -0.5016030364347955 0.16729809310873522 1 -0.8165019880156462 -0.11173420918721436 -0.10363860378347944
    col7 -0.13646519484213326 0.40733726912808044 -0.3858885676469948 0.2900856441586986 0.5496024325711117 -0.29890655828796964 -0.8165019880156462 1 0.07435907471544469 0.11711976051999162
    col8 -0.19500158764680092 -0.11827739124590071 0.20254569203773892 -0.3607547910075688 0.013743256115394122 0.3618518101014617 -0.11173420918721436 0.07435907471544469 1 -0.18463012549540175
    col9 0.3897390240949085 0.12433851389455183 0.13476160753756655 0.4912019074930449 0.07497231559184887 -0.1713960957286885 -0.10363860378347944 0.11711976051999162 -0.18463012549540175 1