help me find a prediction of house price
tamararidwan
New Altair Community Member
hi, i'm new in rapidminer and a student, i have a project to find a prediction of house price from the data i attach here. can anyone please help me to find the accuracy of the house price? since i tried so hard but always meet with rmse.
it would be great if anyone can help me.
thanks
it would be great if anyone can help me.
thanks
0
Best Answers
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Hi @tamararidwan,
The accuracy is a performance metric dedicated to classification tasks.
Prediction of house price, like your project, is a regression task (target variable is continuous). So RapidMiner propose RMSE as performance metric.
However if you want a percentage as performance metrics for your regression task, you have to use (inside your Cross Validation operator) the Performance (Regression) operator and check relative error.
Hope this helps,
Regards,
Lionel2 -
Hello @tamararidwan
@lionelderkrikor already gave some great inputs, one thing to add is squared correlation (R squared, Range between 0 to 1 in rapidminer). The model is better if its closer to 1, most of the time above 0.6 is acceptable and it also depends on the problem domain.
3
Answers
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Can you post your process? Shout if you need help on how to post the code.2
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@robin is this process right? the result is rmse though, i want the result in accuracy percents1
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@robin can you please help?0
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Hi @tamararidwan,
The accuracy is a performance metric dedicated to classification tasks.
Prediction of house price, like your project, is a regression task (target variable is continuous). So RapidMiner propose RMSE as performance metric.
However if you want a percentage as performance metrics for your regression task, you have to use (inside your Cross Validation operator) the Performance (Regression) operator and check relative error.
Hope this helps,
Regards,
Lionel2 -
Hello @tamararidwan
@lionelderkrikor already gave some great inputs, one thing to add is squared correlation (R squared, Range between 0 to 1 in rapidminer). The model is better if its closer to 1, most of the time above 0.6 is acceptable and it also depends on the problem domain.
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@lionelderkrikor @varunm1 hi, i already tried what you said to me, but the result still rmse. can you help me?
thanks.0