How to Handle noisy Data? Binning first sort data and partition into(equal-frequency bins then one can smooth by bin means smooth by bin median, smooth by bin boundaries etc Regression smooth by fitting the data into regression functions Clustering detect and remove outliers Combined computer and human inspection detect suspicious values and check by human(e. g deal with possible outliers)10 How to Handle Noisy Data? ◼ Binning ◼ first sort data and partition into (equal-frequency) bins ◼ then one can smooth by bin means, smooth by bin median, smooth by bin boundaries, etc. ◼ Regression ◼ smooth by fitting the data into regression functions ◼ Clustering ◼ detect and remove outliers ◼ Combined computer and human inspection ◼ detect suspicious values and check by human (e.g., deal with possible outliers)