Learning Fish

  The objective of this experiment is to understand Decision Tree. Decision Tree As the name says all about it, it is a tree which helps us by assisting us in decision-making. Used for both classification and regression, it is a very basic and important predictive learning algorithm. 1. It is different from others because it works intuitively i.e., taking decisions one-by-one. 2. Non-Parametric: Fast and efficient. It consists of nodes which have parent-child relationships The core algorithm for building decision trees called ID3 by J. R. Quinlan which employs a top-down, greedy search through the space of possible branches with no backtracking. ID3 uses Entropy and Information Gain to construct a decision tree. In ZeroR model there is no predictor, in OneR model we try to find the single best predictor, naive Bayesian includes all predictors using Bayes' rule and the independence assumptions between predictors but decision tree includes all predictors with the dependence assumpti...