Highest Rated Posts

varunm1

October 16

Re: Different

Hello @mb223223 If you are asking about deep learning operator (not the extension), yes results change every time unless you select a reproducible option and a local random seed in the parameters. The reason for that is the weight initialization in every run and also the randomness that might change in the model during the…

varunm1

October 10

Re: Help with correct understanding results of classification

Hello @Serek91 There is a concept in machine learning known as the interaction effect. When you analyze your predictors/features, it is not just the independent features that have an impact on algorithm learning but also due to the interaction effect. For example, let's think there are two features A and B, Now if you run…

BalazsBarany

October 10

Re: Help with correct understanding results of classification

Hi! Some partial answers: k-NN might maily learn from a single or few attributes only if you don't normalize the data. (It's comparing values of different attributes directly, so an attribute with a high scale (like 1000) will dominate attributes on small scales (like nominal attributes encoded as 0 or 1).) If this…

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• Different

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  104 views 5 comments 3 points Most recent by User98130 October 17Knowledge Base
• Help with correct understanding results of classification

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