MultiClass Classification using Dense Layers

[tursun]

@jeremy AND janardhanp22,
You have had very interesting conversation.

“I experimented normal machine learning tasks like random forest and getting f1 score (Train)= 0.8602 and fi (Test) = 8138 for the same dataset.”
well, with Fandom Forest, I get F1=0.967 for my data (another dataset similar to tursun_deep_p6.csv).I used RF in Orange.
For my data @janardhanp22 said “since it sounds like you have structured data. In general, deep learning isn’t the best tool for structured data”

Did I find contadict here:
place one:
here, @Jeremy said “do you have structured data. In general, deep learning isn’t the best tool for structured data”

place two:
@sibnick in this webpage:

Multi class classification problem

I suppose your dataset is to small for effective using with CNN, RNN. Also it is not clear nature of parameters. CNN, RNN can be effectively used when parameters have structure (e.g. time series, geometric distribution like pixels in image)

said this to my dataset:
“CNN, RNN can be effectively used when parameters have structure (e.g. time series, geometric distribution like pixels in image)”

my data “tursun_deep_p6.csv” in this webpage:

Multi class classification problem

@jeremy, I am Tursun, a student in Malaysia. I have seen your posts in another thread. But I think this thread is right place. I have this multi-class classification problem. my data : tursun.csv , available to download from here : size of my data set : 512*16, last column is 21 classes, they are digits 1-21 (so maybe OneHotEncoding is not needed) note: number of samples (rows in my data) for each class is different. mostly 20 rows, but sometimes 17 or 31 rows my network has: first la…