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The purpose of this assignment is to apply Linear Regression, Logistic Regression, Support Vector Machine, MultiLayer Perceptron models with regularisation techniques (ridge regression, lasso, elastic net) on Boston Housing Price data set and default of credit card clients data set.

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University College Dublin

Michael Smurfit Graduate School of Business

M.Sc. in Business Analytics

Module MIS41120: Statistical Learning

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Practical Data Analysis

The purpose of this assignment is to apply Linear Regression, Logistic Regression, Support Vector Machine, MultiLayer Perceptron models with regularisation techniques (ridge regression, lasso, elastic net) on Boston Housing Price data set and default of credit card clients data set .

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Distributed under the MIT License. See LICENSE for more information.

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Your Name - hang.nguyen1@ucdconnect.

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The purpose of this assignment is to apply Linear Regression, Logistic Regression, Support Vector Machine, MultiLayer Perceptron models with regularisation techniques (ridge regression, lasso, elastic net) on Boston Housing Price data set and default of credit card clients data set.

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