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Data Analytics & Machine Learning @ Duke | Tech Writer

Credit! A microeconomic equalizer and a double-edged sword in the hands of the wrong regulator. Well thankfully, we’re better than that and in this short article, we will use Multivariable Regression to analyze Credit data of 400 customers in order to predict credit defaults, user profiles, and ratings in the future. The data set is available at http://www-bcf.usc.edu/~gareth/ISL/index.html as a part of the book ‘An Introduction to Statistical Learning with Applications in R’.

Before we get to work on the dataset, let’s emphasize the ‘why’ of this case. We wish to


Nash’s famous point of equilibrium where each player of a bimatrix game(i.e. situation/competition/arrangement) found application much beyond the American bar where its seed was planted (at least in the myopic pop culture lens). Game Theorists argue that it is a legitimate model to define payoffs and structure strategies (mixed or pure) in order to reach a point where players do not have an incentive to play in any other way. …

Fractally Speaking

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