🦉 🎤   RapidMiner Wisdom 2020 - CALL FOR SPEAKERS   🦉 🎤
We are inviting all community members to submit proposals to speak at Wisdom 2020 in Boston.
Whether it's a cool RapidMiner trick or a use case implementation, we want to see what you have.
Form link is below and deadline for submissions is November 15. See you in Boston!
"More neurons in hidden layer wont increase/decrease neural network performance"
i used the search function but found nothing.
I'm using RapidMiner 5.1.003
Data Mining Setup is as following:
i've used 7 different datasets from the uci repository (wine,adult,krkrpa7,iris,house-votes-84, heart-cleveland and zoo) for a classification task. In all of those i meassured performance using cross-validation (10 validations, shuffled or linear sampling)
In all of those i was wondering why an increase in hidden layer neurons wont have any impact on the result. With more hidden neurons it should perform better unless it's overfitting. Am i wrong somewhere?Is this just concerning the free community edition?
The neural network model in average works fine, i was just wondering why there is no slight increase/decrease in performance.
thanks for reading & have a nice day