We are happy to announce iNeuron is coming up with the 6 months Live Full Stack Data Analytics batch with job assistance and internship starting from 18th June 2022.The instructor of the course will be me and Sudhanshu. The course price is really affordable 4000rs Inr    including GST.
The course content will be available for lifetime along with prerecorded videos.
You can check the course syllabus below
Course link: https://courses.ineuron.ai/Full-Stack-Data-Analytics
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मंडळ आभारी आहे

decision tree for both classification regression here classification. 2 techniqiues. ID3 and CART. In Cart the decision tress spilts into binary trees. a)Entropy and Gini Index(Purity spirit) b) Information Gain(feature decision tree split). To check for Pure split two techniques called Entropy and Gini impurity are used and second technique called INformation gain (how the features are selected) is used.
When H(S) is zero then that is pure split. And when H(s) is 1 then that is impure split ie equal distribution (eg 3yes and 3nos). The range of entropy remains between 0 to 1.

In impure split the Gini impurity comes out to be 0.5 and in pure split it is 0. So the gini impurity ranges between 0 to 0.5. So in impure split the max value of gini impurity is 0.5 and in pure split it is 0.

gini impurity is preferrable over entropy because of involvement of log it may slow down

Now if you have multiple features, you use information gain to know how to make the tree using the given features whether which feature will start and which one will follow later. The feature starting with which the information gain calculation comes out to be the most should be the one with which the decision tree should be started.

Searching for the topic for many hours suddenly found krishna sir ❤😊

Thanx sir in Hindi explanations you tend to cover topics better(English vedios  are also of  far better quality than anyone else)

It is one of the best and simplest explanations till far

after one an era  No one will beat you sir !! incredible explanation thankyou so much sir

Worth watching😍😍😍

Great explaination...hard to find anywhere else👌👌

in one word bosssss <3

your teaching skill awesomwe.

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Good style of explanation 😁

That was awesome

Awesome Explanation....Thanks A Lot....Keep It Up !!!

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thankyou..sir😇

hello krish sir... your explanation is easy to understand and anyone can learn easily..thank you sir...😊

best tutorial of decision trees

Thanks Krish, Best Ever Video, Wao.