How to find the Entropy and Information Gain in Decision Tree Learning by Mahesh Huddar

How to find the Entropy and Information Gain in Decision Tree Learning by Mahesh Huddar

In this video, I will discuss how to find entropy and information gain given a set of training examples in constructing a decision tree.

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[terryterry]

HI sir this is best explanation i have seen so far. in my Datascience i shared this link to my friends . thanks for your support and
in Issues in Decision Tree Learning. can u pls post the ans for last two questions ( handling arributes with different costs
and
alternative measures for selecting attributes )

[sachinahankari]

How root node depends on information gain of attributes.?.. Simply super Explanation..If you get questions from listeners.. You understand that they like your videos

[purplishjen]

Thank you so much! I was able to submit my assignment in my masters because of this video

[shiva]

To achieve Entropy = 0.94, you need to divide the whole answer solved by taking ln X by ln 2, because log X base 2 = ln X / ln 2

[wryltxw]

your presentation is excellent and clear. thank you for making these videos available to everyone.

[maheshm]

Clean and neat explanation Thank you sir

[ashutoshmahajan]

I am a masters student of data science at a german university and this has helped me thoroughly for my ML exam! Thank you dear sir!

[vighneshchavan]

Thank you very much sir, completely cleared my doubt.

[loveparks]

This was so easy to understand!! Thank You so much

[prateekmishra]

very lucid explanation. Thanks a ton Prof.

[avanishkamak]

Thank you so much very simply explained

[unique_bhanu]

Can you explain this "One interpretation of entropy from information theory is that it specifies the minimum number of bits of information needed to encode the classification of an arbitrary member of S.

[blessaddo]

Ahh here i am revising for my final Data mining exam, wish me luck

[aarushgandhi]

since we are calculating entropy for a given dataset from one column only that is our classification, thus we could say entropy for a given dataset remains same when we calculate it for each column as no. of yes and no remains same? please answer fast

[EndlesRidge]

Hello Sir, awesome job on this video.

[husnain]

Reply please
I have some doubt on how to calculate the term log base 2 . How to do this calculation. Means 9/14 log base 2 9/14 - How to achieve the answer like 0.94

[bollytainment]

How to calculate gain and entropy of continuous data?
Is it possible to do so ?