Do you have any idea what the root of this could be?

Maybe the error is on our side?
You can find our implementation in Filter.R.

PS: It is very nice that praznik is so fast!

See https://github.com/mlr-org/mlr/issues/2604
Do you have any idea what the root of this could be?
Maybe the error is on our side?
You can find our implementation in [Filter.R](https://github.com/mlr-org/mlr/blob/659d72c6c8e1ea5e93555fb7dd1d4c1405431355/R/Filter.R).
PS: It is very nice that `praznik` is so fast!

AFAICT, mRMRe calculates mutual information by estimating from correlation between features, using the formula I(x,y)=−.5 log (1−cor(x,y)^2) (this is why it expects numerical input), while praznik from a direct formula I(x,y)=p_xy log (p_xy/p_x/p_y) for categorical variables (and this is why it expects factors)... So these are basically different algorithms, or let's say, versions of mRMR using different interface to the data.

AFAICT, mRMRe calculates mutual information by estimating from correlation between features, using the formula `I(x,y)=−.5 log (1−cor(x,y)^2)` (this is why it expects numerical input), while praznik from a direct formula `I(x,y)=p_xy log (p_xy/p_x/p_y)` for categorical variables (and this is why it expects factors)... So these are basically different algorithms, or let's say, versions of mRMR using different interface to the data.

See https://github.com/mlr-org/mlr/issues/2604

Do you have any idea what the root of this could be?

Maybe the error is on our side? You can find our implementation in Filter.R.

PS: It is very nice that

`praznik`

is so fast!AFAICT, mRMRe calculates mutual information by estimating from correlation between features, using the formula

`I(x,y)=−.5 log (1−cor(x,y)^2)`

(this is why it expects numerical input), while praznik from a direct formula`I(x,y)=p_xy log (p_xy/p_x/p_y)`

for categorical variables (and this is why it expects factors)... So these are basically different algorithms, or let's say, versions of mRMR using different interface to the data.