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Supervised Learning

This Project has the implmentation of the supervised learning algorithms and they are

  1. Decision Trees
  2. Artificial Neural Networks
  3. K-nearest Neighbours
  4. Support Vector Machines
  5. Boosting/bagging

The supervised learning algorithms are being implemented on the Bank Churn dataset which has the records of the customers of the bank which have stayed or exited the bank. The data is of 6 months time period.

The code does all the hyperparameter tuning for all the learning algorithms to get the best accuracy. The code can be used to study in detail about the behaviour of all the algorithms and which learning algorithm can be better for which type of dataset. The comparisional study gives a lot of insight of the learning algorithms.