File [code_convergence.py]:
To evaluate the convergence rate, run it as 'python code_convergence.py DATASET', where DATASET can be 'Iris', 'BC', 'CC', 'Bank', and 'Adult', represents datasets Iris, Breast Cancer, Credit Card Fraud, Bank, and Adult, respectively.

File [code_dimension.py]
To evaluate the effects caused by dimension p, run it as 'python code_dimension.py DATASET', where DATASET can be 'CC', 'Bank' and 'Adult', represents datasets Credit Card Fraud, Bank, and Adult, respectively.

File [code_classify.py]
To evaluate the effects caused by privacy budget $\epsilon$, run it as 'python code_classify.py DATASET', where DATASET can be 'Iris', 'BC', 'CC', 'Bank', and 'Adult', represents datasets Iris, Breast Cancer, Credit Card Fraud, Bank, and Adult, respectively.