Comma values - best predictive model suggestion

Bambo
Bambo New Altair Community Member
edited November 2024 in Community Q&A

Hello, I would like to know what is the best predictive operator to solve my problem.

 

input_output_comma.PNG

 

So my main goal is to find the best predictive operator which could handle comma values (Input 1, Input 2, Input 3) and values in "Input 4" column (YES/NO) and predict values in "Output" column. I already tried Optimize Parameters(Evolutionary) with operators like [SVM kernel types: (radial, anova, epachenikov etc), Random Forest, Neural Net, Decision Tree] to find optimal values, but the average accuracy of prediction was low.

 

I would really like to know if someone could suggest some predictive operator which could produce the best accuracy for this kind of problem.

NOTE: The values in columns "Input 1, Input 2, Input 3" after adding up always equals 100% in every row if this helps.

Thanks very much in advance.

Answers

  • Pavithra_Rao
    Pavithra_Rao New Altair Community Member

    Hi @Bambo,

     

    You could try new 'Auto Model' feature to find the best predictive model for given data set.

     

    RapidMiner Auto Model

     

    Cheers,

  • kypexin
    kypexin New Altair Community Member

    Hi @Bambo

     

    For me, it would matter if the output column represents an arbitrary integer value or a categorical value (and in the latter case, how many unique categories you can have). If it's categorical, you could possibly use any non-linear algorithm like decision tree / RF / GBT. If it's numerical, then regression models would fit, but most likely you'll have to transform boolean column then.

     

    Generally speaking, you still have to experiment with different models and compare results.