Tutorial 37: Entropy In Decision Tree Intuition

Entropy gives measure of impurity in a node. In a decision tree building process, two important decisions are to be made — what is the best split(s) and which is the best variable to split a node.

Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below
amazon url:

Connect with me here:

Subscribe my unboxing Channel

Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning!

You can buy my book on Finance with Machine Learning and Deep Learning from the below url

🙏🙏🙏🙏🙏🙏🙏🙏
YOU JUST NEED TO DO
3 THINGS to support my channel
LIKE
SHARE
&
SUBSCRIBE
TO MY YOUTUBE CHANNEL

[shivadumnawar]

One of the great teacher in the Machine Learning field. You are my best teacher in ML.Thank you so much sir for spreading your knowledge.

[SALESENGLISH]

I checked all the codes in your book. Everything works like charm. I can guess that you have mastered Machine Learning by struggling through it. Those who are spoon-fed cannot be half as good as you. Great job! We wish you all the success.

[aaroncode]

This is what I was looking for. Thank you so much for making this video. Eagerly wait for video on information gain. Please keep going 🙏

[yamika.]

thank you. we all need teachers like you. god bless you. you're a blessing for us college students who are struggling with offline colleges after the reopening.

[ABINASHPANDA-beug]

Hi, there might be calculation mistake in the entropy part. its not 0.78. Can you please mention that in a caption in the video or a description. So that people dont mistaken it in the future. Great video!!

[rchilumuri]

You are doing an awesome job with our expecting returns. good job Krish, You just nail down the concepts in a line or two thats the way i like it.

[mdrashidansari]

You cleared my all doubts about Excellent Explanation 😍😍😍😍

[sameerkhnl]

Thank you for a great tutorial. The entropy value is actually 0.97 and not 0.78.

[sandipansarkar]

Good explanation Krish.Now my misconceptions about decision trees is dwindling away.Thanks

[ayberkctis]

You clearly explain the mathematics of machine learning algorithms! Thank you for your effort.

[bhavikdudhrejiya]

Best channel for Data Science Beginners

[maximumthefirst]

Thanks for the video. At 05:48, how does -3/5log2(3/5)-(2/5log2(2/5)) equal 0.78 ??? I think the correct answer ist 0.971

Could you explain?

[cequest]

You should start explaining from the root node.. Like take entropy of all f1, f2, f3 first.. then select the best one as the root node, then calculate entropy for remaining data for f2 and f3, and select next best entropy as the node... and continue the same process

[keamogetsethaoge]

Thank you Thank you Thank After this I am ready for my test tomorrow.... You are boss with these concepts!!.. Please keep making more. I''ll definitely subscribe and share with friends.

[VivekKumar-nffh]

Nice explanation.... But looking for deep learning video..Please don't stop DL in-between

[abdulkayumshaikh]

Explained in a great way ...Thank you krish

[AbhishekRana-yeuw]

very much helpful sir thank you you are best :)

[lekhnathojha]

very well understandable your teaching curriculum.

[Lavanya-pe]

This is one of the best explanation thankyou somuch sir

[hemantsharma]

Hi Sir, this video is 37th in ML playlist but we don't have any decision tree video before it.