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How to interpret 'cost' column in classifications

Hi Im new to this whole world and am using rapid miner go. I set up a deep learning model for classification. In the output when I apply my model to a new data set the first column that shows is 'cost'. I assumed that has to do with the 'gain and cost' payoff table that I set up when creating the model, but it doesnt seem to match with what I'd expect to see given the inputs I put in.

Can any one help me on how to interpret this 'cost' column or how it is calculated.

Thank you!

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Accepted answers

MartinLiebig

Hi,

this should be the lowest cost, where cost is defined as confidence*cost_in_matrix.

Best,

Martin

All comments

MartinLiebig

Hi @cramsden ,

sure! its the calculation we talk about here: https://rapidminer.com/resource/profit-sensitive-scoring/ . maybe there is a minus sign somewhere, because sometimes you talk about costs, and sometimes about gains.

Best,

Martin

cramsden

Yes, I understand setting up the cost benefit table. But I'm asking more for the cost column in the output when I apply the model to new datasets (I'll attach a screen shot). I think I am interpreting this wrong because if I have 2 different models one with the default (+1,-1) payoff table, and another which i adjust to +1,-10000 just to see how that effected the cost column in the output. I expected to see the cost column be large negative numbers with this set up but they were not. That's why I am a bit confused, I cant find any documentation on this.

Image: https://us.v-cdn.net/6030995/uploads/editor/us/c7ro9ekz35p6.png

MartinLiebig

Hi,

this should be the lowest cost, where cost is defined as confidence*cost_in_matrix.

Best,

Martin

cramsden

Thank you! Figured it out!!