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Machine learning

NON-PARAMETRIC TESTS

NON-PARAMETRIC TESTS Within a parametric framework at first we assume an explicit functional form of the population distribution function which is labelled by a parameter ϴ where ϴ is unknown or not completely known and subsequently any…

Naive Bayes Classifier

Introduction To Naive Bayes Naive Bayes has its foundation pillar from the concept of Bayes theorem explained by the theory of probability. Probability is the chance of an event occuring. Probability can related to our regular life and it…

Decision Tree

Decision Tree Introduction A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display…

Random Forest

CART (Classification and Regression Trees) An Introduction and Motivation for choosing CART: Two of the very basic ideas behind any algorithm used for predictive analysis are : - prediction on the basis of regression and prediction on the…