In the decision tree based classification technique. What is the difference among the different approaches like entropy, gini index? When to use entropy and when to use gini index?.
Here is a quote from a paper on the subject:
Different split criteria were proposed in the literature (Information Gain, Gini Index, etc.). It is not obvious which of them will produce the best decision tree for a given data set. A large amount of empirical tests were conducted in order to answer this question. No conclusive results were found.
Raileanu, L. E., & Stoffel, K. (2004). Theoretical Comparison between the Gini Index and Information Gain Criteria. Annals of Mathematics and Artificial Intelligence, 41(1), 77-93. Kluwer Academic Publishers.