I'm new in data analysis area and didn't have very strong statistical background...
Now, I'm trying to filter out those numeric columns which have high correlation. At this moment, I don't plan to use dimensional reduction algorithms such as PCA because I'm still collecting data, and there are too many columns, I hope to remove some columns first before linking different sources of data together.
Playing with PCA and machine learning models will be after linking those sources of data.
So, at this "before" stage, I'm trying to use R
findCorrelation() method, but I could not find how does this method work.
Now my question is, I should use this method after data cleaning (such as, deal with missing data, outliers, data imbalance) or it doesn't matter to do it before or after?