random forest

Bootstrap Sample

Before we discuss about Bootstrap Sample, read about Sampling With Replacement and Sampling Without Replacement A bootstrap sample is a random sample that is performed with replacement. Bootstrapping is a resampling with replacement which uses sampling with replacement, It will generate N number of samples and each sample is the same size of population. Let’sContinue reading “Bootstrap Sample”

Before we discuss about Bagging and Random forest we have to understand about Bootstrap sample. Bagging: Is also called bootstrap aggregator it gives best accuracy than decision tree and to reduce the variance. Bagging is very easy when you know how Decision tree and bootstrap sample works.It will use the greedy search algorithms like Entropy, Gini,Continue reading “Random Forest”

Pruning

Practically, post-pruning overfit trees is more successful because it is not easy to precisely estimate when to stop growing the tree.In this article we will see how to overcome overfitting problem using Post pruning. We need to follow below steps in order to prune a full grown tree Here we willContinue reading “Pruning”