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Gradient boosting weights

Hi all,
I ran the model with gradient boosting algorithm in rapid miner and I have seen the weights generated for each input parameter and some of them have zero weight does that mean that those are eliminated from the model.does that mean it feature selects the parameters with positive weight?
Could you please help me in this.

Regards
Vishnu

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Accepted answers

MartinLiebig

Hi,

yes and yes, i would call it feature selection. I often use this (or the weights of an RF) for feature selection. Just use a Select by Weights operator afterwards.

Best,

Martin

All comments

MartinLiebig

Hi @k_vishnu772,

the weights are caculated in the aftermath. Basically you run over all trees an calculate the influence of each cut and sum over it. A value of 0 in the weights indicates, that this attribute was never used for any split.

Cheers!

Martin

k_vishnu772

@mschmitz

so attibute of weight zero means even if i remove those in the model i should be able to get the same results right ?

and it is a kind of feature selection

MartinLiebig

Hi,

yes and yes, i would call it feature selection. I often use this (or the weights of an RF) for feature selection. Just use a Select by Weights operator afterwards.

Best,

Martin