Question

How  to  find an attribute, which is  the best classifier using information gain. 

Cite an example​

Answer 1

Answer:

What Is Information Gain?

Information Gain, or IG for short, measures the reduction in entropy or surprise by splitting a dataset according to a given value of a random variable.

A larger information gain suggests a lower entropy group or groups of samples, and hence less surprise.

You might recall that information quantifies how surprising an event is in bits. Lower probability events have more information, higher probability events have less information. Entropy quantifies how much information there is in a random variable, or more specifically its probability distribution. A skewed distribution has a low entropy, whereas a distribution where events have equal probability has a larger entropy.

In information theory, we like to describe the “surprise” of an event. Low probability events are more surprising therefore have a larger amount of information. Whereas probability distributions where the events are equally likely are more surprising and have larger entropy.