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Training 3 machine learning algorithms on the Indian Liver Patient Disease (ILPD) Dataset to find out which features play a role in determining if a patient has liver disease.

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Project: Predicting Liver Disease from data

Problem Statement Given a dataset containing various attributes of 583 Indian patients, define a classification algorithm which can identify whether a person is suffering from liver disease or not.

Solution Statement To solve this problem, I will be using Logistic Regression, Support Vector Machine, knearest neighbours and one ensemble method. Different combinations of hyperparameters for individual algorithms , like kernel, degree and C for SVM and weights, n_neighbours and algorithms for k-Nearest Neighbours will be tried across the training sets. Depending on their respective performances on the cross-validation sets, the best algorithm with appropriate hyperparameter tuning will be finalised as the solution.

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Training 3 machine learning algorithms on the Indian Liver Patient Disease (ILPD) Dataset to find out which features play a role in determining if a patient has liver disease.

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