Platform For AI:Linear Regression

Configure the component

You can use one of the following methods to configure the Linear Regression component.

Method 1: Configure the component on the pipeline page

Method 2: Use PAI commands

PAI -name linearregression
    -project algo_public
    -DinputTableName=lm_test_input
    -DfeatureColNames=x
    -DlabelColName=y
    -DmodelName=lm_test_input_model_out;

Example

1. Execute the following SQL statements to generate test data:

    drop table if exists lm_test_input;
     create table lm_test_input as
     select
       *
     from
     (
       select 10 as y, 1.84 as x1, 1 as x2, '0:1.84 1:1' as sparsecol1 from dual
         union all
       select 20 as y, 2.13 as x1, 0 as x2, '0:2.13' as sparsecol1 from dual
         union all
       select 30 as y, 3.89 as x1, 0 as x2, '0:3.89' as sparsecol1 from dual
         union all
       select 40 as y, 4.19 as x1, 0 as x2, '0:4.19' as sparsecol1 from dual
         union all
       select 50 as y, 5.76 as x1, 0 as x2, '0:5.76' as sparsecol1 from dual
         union all
       select 60 as y, 6.68 as x1, 2 as x2, '0:6.68 1:2' as sparsecol1 from dual
         union all
       select 70 as y, 7.58 as x1, 0 as x2, '0:7.58' as sparsecol1 from dual
         union all
       select 80 as y, 8.01 as x1, 0 as x2, '0:8.01' as sparsecol1 from dual
         union all
       select 90 as y, 9.02 as x1, 3 as x2, '0:9.02 1:3' as sparsecol1 from dual
         union all
       select 100 as y, 10.56 as x1, 0 as x2, '0:10.56' as sparsecol1 from dual
     ) tmp;

2. Run the following PAI command to submit the parameters configured for the Linear Regression component:

   PAI -name linearregression
       -project algo_public
       -DinputTableName=lm_test_input
       -DlabelColName=y
       -DfeatureColNames=x1,x2
       -DmodelName=lm_test_input_model_out
       -DoutputTableName=lm_test_input_conf_out
       -DenableCoefficientEstimate=true
       -DenableFitGoodness=true
       -Dlifecycle=1;

3. Run the following PAI command to submit the parameters configured for the Prediction component:

   pai -name prediction
       -project algo_public
       -DmodelName=lm_test_input_model_out
       -DinputTableName=lm_test_input
       -DoutputTableName=lm_test_input_predict_out
       -DappendColNames=y;

4. View the generated model evaluation table lm_test_input_conf_out.

   +------------+------------+------------+------------+--------------------+------------+
   | colname    | value      | tscore     | pvalue     | confidenceinterval | p          |
   +------------+------------+------------+------------+--------------------+------------+
   | Intercept  | -6.42378496687763 | -2.2725755951390028 | 0.06       | {"2.5%": -11.964027, "97.5%": -0.883543} | coefficient |
   | x1         | 10.260063429838898 | 23.270944360826963 | 0.0        | {"2.5%": 9.395908, "97.5%": 11.124219} | coefficient |
   | x2         | 0.35374498323846265 | 0.2949247320997519 | 0.81       | {"2.5%": -1.997160, "97.5%": 2.704650} | coefficient |
   | rsquared   | 0.9879675667384592 | NULL       | NULL       | NULL               | goodness   |
   | adjusted_rsquared | 0.9845297286637332 | NULL       | NULL       | NULL               | goodness   |
   | aic        | 59.331109494251805 | NULL       | NULL       | NULL               | goodness   |
   | degree_of_freedom | 7.0        | NULL       | NULL       | NULL               | goodness   |
   | standardErr_residual | 3.765777749448906 | NULL       | NULL       | NULL               | goodness   |
   | deviance   | 99.26757440771128 | NULL       | NULL       | NULL               | goodness   |
   +------------+------------+------------+------------+--------------------+------------+

5. View the prediction result table lm_test_input_predict_out indicated by the following code:

   +------------+-------------------+------------------+-------------------+
   | y          | prediction_result | prediction_score | prediction_detail |
   +------------+-------------------+------------------+-------------------+
   | 10         | NULL              | 12.808476727264404 | {"y": 12.8084767272644} |
   | 20         | NULL              | 15.43015013867922 | {"y": 15.43015013867922} |
   | 30         | NULL              | 33.48786177519568 | {"y": 33.48786177519568} |
   | 40         | NULL              | 36.565880804147355 | {"y": 36.56588080414735} |
   | 50         | NULL              | 52.674180388994415 | {"y": 52.67418038899442} |
   | 60         | NULL              | 62.82092871092313 | {"y": 62.82092871092313} |
   | 70         | NULL              | 71.34749583130122 | {"y": 71.34749583130122} |
   | 80         | NULL              | 75.75932310613193 | {"y": 75.75932310613193} |
   | 90         | NULL              | 87.1832221199846 | {"y": 87.18322211998461} |
   | 100        | NULL              | 101.92248485222113 | {"y": 101.9224848522211} |
   +------------+-------------------+------------------+-------------------+