Machine Learning Tutorial 6 - Decision Tree Classifier and Decision Tree Regression in Python

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In this video, we will learn about decision tree Machine learning in python. A decision tree is a flowchart-like tree structure where an internal node represents a feature, the branch represents a decision rule, and each leaf node represents the outcome. The topmost node in a decision tree is known as the root node. It learns to partition on the basis of the attribute value. It partitions the tree in a recursive manner called recursive partitioning. This flowchart-like structure helps you in decision making. It’s visualization like a flowchart diagram that easily mimics human-level thinking. That is why decision trees are easy to understand and interpret.

🔊 Watch till last for a detailed description
02:09 What is the decision tree?
06:42 Why the decision tree?
11:08 Attribute selection measures in the decision tree
15:36 Decision tree regressor
30:35 Decision tree as a classifier

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Tks for showing both Regression and Classification example in the video. You always try to cover most of the possible variations/options of the algorithm, that's very helpful. Tks once again.

yogeshbharadwaj

Thank you so much for the effort that you are putting to create these videos. I can see You are always descriptive and informative in each of your videos 😀

bibaswanpadhi

Thank you so much Laxmikant ji for this wonderful video.
These videos are really in detail and very helpful.

himanshudalai

i am not able to access the working code

Saravananmicrosoft

Also Laxmi ji..can you make a video on Git & Github. The video can be a beginner's manual for how to use it for building one's profile. It will be really helpful. Thank you.

himanshudalai

kindly sens us the link to download the code. on every video i had commented on this part.. but no response as of now. kindly upload the link.. thanks in adv.

dibyarashmisahoo

Plz kindly request because without whole data we can't do proper learning of yours all videos

sandeepmane

Send all data set have used for all machine learning algorithms

sandeepmane

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