I have data that contains 500+ columns and 700+ rows.
I want to know the best 20 Columns that I can process to the next modeling, namely Regression Logistics.
I’m trying to figure out what I can apply to find the best 20 columns out of these 500+ columns and find PCA. The PCA technique is very new in my opinion.
Can anyone explain or provide reading references that are suitable for beginners like me about how PCA performs in KNIME and what if I continue the results obtained from PCA to Regression Logistics?