"[WRONG CALCULATION?] Linear Regression Output"

Sharlto

Hi guys,

I'm a new user of RapidMiner and a newbie in data mining.
I try to built a linear regression model and compared the result it with R.
I quite shock when I get a different result from R for Std. Error and t value.

I have change feature selection to: none and ridge to 0

Is there anybody can help me to explain it?
Am I wrong to read the output?

Below is result from RM
Attribute: AGST
Coefficient: 0.635
Std. Error: 0.031
Std. Coefficient: 0.026
Tolerance: 1
t-Stat: 20.221
p-Value: 0

Result from R
AGST
Estimate: 0.6351
Std. Error: 0.1509
t value: 4.208
Pr(>|t|): 0.000335

earmijo

If you want us to help you, provide the dataset or a subset of the dataset so we can replicate the problem.

Sharlto

Hi earmijo,

It's interesting that there is another people experiences a same thing like me but he was using SPSS
http://www.researchgate.net/post/Why_are_the_output_values_for_simple_linear_regression_using_RapidMiner_different_from_other_software

I think we can use any data as dataset and compare the linear regression result with another statistic software.
I'm afraid the problem is in how RapidMiner do the calculation for Standard Error and t-Stat

I want to attached my dataset but don't know how to attach my file.

MartinLiebig

could you please try out vector linear regression instead of linear regression?

Edit: This is not returning T-test values

Sharlto

Hi Martin,

I have tried using vector linear regression as you suggested but the problem is not in the coefficient. The problem is not in the coefficient but in Std Error, T Stat and P-Value.

Have you try to compare the output result (Std Error, T Stat and P-Value) from RapidMiner and another Statistic package?

Anyway how to upload a dataset?