Decision Tree

When learning about Decision tree, I learned about Entropy. In my opinion, entropy is important to learn for data science and in decision tree. In simple words, entropy is the measurement of level of impurity in the data set or it is measurement of uncertainty. It is defined as Entropy = – p(a)*log(p(a)) – p(b)*log(p(b)) The … Continue reading Decision Tree