Decision Tree: Important things to know

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#MachineLearning #Deeplearning #DataScience

Decision tree organizes a series rules in a tree structure. It is one of the most practical methods for non-parametric supervised learning. Our goal in this video is to demonstrate how to create a decision tree that predicts the value of a target by learning decision rules inferred from the training data.

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Комментарии
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Unbelievable. I am astonished at how simple and concisely this algorithm is explained in a very limited amount of time by all this hard work to create such a video, presumably. Great job!😄

adoanmian
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Keep going, man, your explanations is amazing!

vladmosiychuk
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Really good explanation, thx ... I hope to see for the next video a deepen about Random Forest and how to assess the quality of the algorithm

DigitalMadness
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You have made this concept so easy to grasp. Great work! 😄

jerushagomez
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Highly appreciated!
Thanks and keep going!

ashutoshdave
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At 2:34 for the right hand expression for "Information Gain", don't you think that last "/2" shouldn't be there as you are taking the weighted average already in the parentheses?

Also, I wanted to acknowledge how concise and informative your videos are. Keep up the great work! Thanks!

shuvragupta
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Bro making of video is extraordinary can I know the softwares that you are using to make your videos..

PlayWithCoding
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Now waiting for Random Forest, great Explanation.

visheshsinha_
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great explanation 👌🏼 thank you for the effort :)

message
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Thanks man.
How are the decision rules for numeric features decided especially if the range of values is large?

pratyushbehere
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which software have you used for animation ?

faique
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Heyy, are you still using Manim for your animations?

RahulGupta-vwjr
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I disagree with those people who say "great explanations". The talk is too fast and I find the path of explanation not clear, I can't follow it and therefore understand nothing.

adsick_ua
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Noise background added, didn't watch.

skk
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True should be on the left and False on the right and you showed it the opposite way. If you don't understand the basics you should not explain because you are wasting people's time by providing wrong information.

alabsinatheer