You should clean the data, remove outliers and then run the algorithms you have learned on the
data. For numeric attributes, you can calculate min, max, average, standard deviation, and covariance/correlation. If the attributes are nominal, then you can calculate the frequency of each
label. If the attributes are of mixed (numeric and nominal) type, then you can convert numeric to
nominal using filters or using some other meaningful translations (for example, convert numbers
to ranges like “low”, “medium”, and “high”). You can then apply different methods for
classification, clustering, outlier detection, data mining and regression methods.
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