I used predictive tools: linear regression and random forest to predict.
With the same source data, the same target and predictor variables, assist modeling tool generated a big different result (16% variance for LR).
I understand one uses R, the other uses Python. Thus, the results cannot be exactly the same.
However, the statistical theory behind the scenes should be the same.
I wonder what drives the big difference between using assist modeling tool and predictive tool?
I have attached the workflow for your reference.
Thanks
Solved! Go to Solution.
Hi @Gualigee
Please check the hyper parameter.
For example, Linear Regression of Intelligent suites is set as Fit Intercept is On and Normalize is On.
But the Linear Regression of R based tool is set as all off.
If you use the same hyper parameter between R based tool and intelligence suites, the difference will be smaller.
Thanks, @AkimasaKajitani it makes sense now. You rock!
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