Performs chi2 and mutual information tests on the bank dataset to find the most relevant categorical and numerical attributes.
The dataset (bank-additional-full.csv) is related to direct marketing campaigns of a Portuguese banking institution. The classification goal is to predict whether a client will subscribe to a term deposit. Obtained from https://archive.ics.uci.edu/ml/datasets.html
chi2test.py: Performs chi2 test on categorical attributes
MutualInformation.py: Performs mutual information test on numerical attributes
barchartplot.py: Plots bar chart for the categorical attribute entered by the user. Plot_Education.html shows the bar chart for the education attribute.
OneHot.py: Converts the categorical attributes into their one-hot representation
Normalization.py: Performs normalization on numerical attributes to ranges [0,1], [-1,0] or [-1,1]
classdistribution.py: Plots bar chart of the class attribute i.e. whether a client will subscribe to a term deposit.