How to Handle noisy Data? Binning first sort data and partition into(equal-frequency bins o 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 ■C| uttering detect and remove outliers Combined computer and human inspection o detect suspicious values and check by human(e.g deal with possible outliers) 同济大学软件学院 10 ool of Software Engineering. Tongpi Unversity10 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)