Decision Tree Regression in Python (from scratch!)

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How about creating a decision tree regressor without using sci-kit learn? This video will show you how to code a decision tree to solve regression problems from scratch!
#machinelearning #datascience #python

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(Donor: Dr Roberto Lopez
Intelnics
Creators: Thomas F. Brooks, D. Stuart Pope and Michael A. Marcolini
NASA)

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you are doing a great work, the videos are really helpful, keep up the good work!!

piyushnashani
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i am watching from Brazil, great video

torvess
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Just beautiful! Thank you so much for all your effort, it is greatly appreciated! <3

dominiquedewet
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you make videos so quickly, keep up the good work!!!

averyiorio
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Thank you so much for the awesome explanation!

rishabhjain
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Please make a video on decision tree using grid search cv and explaining all the hyperparameters of it

mohandev
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Please make a complete series on how you create such astonishing animations to explain the concepts ...I think you use manim library of python...It would be of great help

nipunkulshrestha
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This is a great video! I have watched all your decision tree videos, but i still wondering how to make decision tree regression or classification if you have categorical data on it?

keshia
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if the max depth is too high, I get a key error during the best split routine. Is there a way to fix that?

g_arm_
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why do you use variance reduction? I see other sources use sum of squared errors for splitting

juanrenatojimenezpasache
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Thanks for the great videos. A question though. To quantify accuracy of your predictions, you use RMSE which is not a dim-less measure of error. I am just wondering about the value of RMSE normalized with mean(Yi). Thanks again.

amirtaghavy
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hello, I have a problem please, when I wrote the codes jupyter said " invalid syntax" !!!!, for the first codes of partition"class Node'', any help, please

maryamazeez
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beside the airfoil csv, can i apply other data and apply to this model ?

TTS
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can you help me convert the variance_reduction to a calculation of SSR ?

TheTOMAVITAN
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Hello, very nice video!
Is there a way to say this model r2 values is above .7 or something in decision tree regression model? if yes, how we can extract that r2 in case of your given example?

_jakiya_hereweare