Information gain is the concept used to select variables that is used for classification in decision trees.
Is the quantity of information the most important part of information gain or is the quality of the information obtained more important?
IMO, Quality of the information that determines entropy, which in turn determines information gain is more important than the quantity of the input information but I just wanted to make sure my thoughts..
Dear Sathish,
In any data based decision making process, "clutter" always creates more problems than it solves. The quantity of information therefore is actually irrelevant. The quality of information is THE most important factor.
However, I would like to add two factors - reliability and verifiability. If the information is from sources that have the correct ingredients to generate the information, then it would be reliable. Not withstanding that it has come from a reliable source, if there is a alternate channel through which information can be cross-checked, then it would stand the test of verifiability.
The adage "brevity is the soul of wit" is worthy of remembrance. Hope this helps.
Have a great day.
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