Regression Trees | Decision Trees Part 3

[@ali75988]

19:00 I do believe there is some problem in the plane cutting part. The graph in 2d was between hours and marks and cut was based on hours (vertical line). When it goes to 3d, it cuts along x-axis, rather than y-axis (vertical or b/w no of hours and marks, but cutting hours line).
Same is the case with other plane.

[@anshkapoor4990]

i do think the same, just in case you found you answer pls elaborate (any info will be helpful)

[@jamitkumar7251]

19:53 i think there's a slight mistake, the plane perpendicular to hours axis will split the data. :)

[@GamerBoy-ii4jc]

kmaal he Sir g..apny buhat acha arrange kea hua sb videos ko...agr Linear Regression k sth lgaa dety isko to smjh na ati complete Decision Tree concept ly kr kmal smjh aa ri he Great one!

[@shwetakumari2216]

Thank you for such nice intuitive video
But I got some questions that I'm very curious about and it will be really kind if you can Ans them
1. At 6:30 can we apply polynomial regression as it is a 2D data??
2. In case of 2 D what to prefer polynomial or regression tree??
3. At 18:43 since we are comparing SSE for marks and SSE for hrs, so do we need feature scaling.
As in decision tree we don't need it , is it same with regression tree??

[@pythonista_]

Using polynomial regression on the large datasets is a bad idea because it create more number of features suppose if your dataset you have 50 features suppose you set degree as 4 in that scenario 50 *4 = 200 features are created

[@kindaeasy9797]

wekk about your 3 rd question , i dont think we comapre columns using SSE in DT regression, there is some metric called variance reduction

[@rockykumarverma980]

Thank you so much sir🙏🙏🙏

[@studology67]

When splitter is set to random, toh jis feature mai split karna hai wo bhi randomly select hota hai kya?

[@sudiptasaha7427]

Sir, please explain about adjusted Rsquare in case of regression tree with formula

[@HimaniHimani-b1t]

Hats off to your effort sir

[@hasanrants]

completed on 3:48PM, 20th September 2024.

[@balrajprajesh6473]

thank you so much sir!

[@kushh7550]

Thanks Sir

[@AbdulRahman-zp5bp]

Thanks sir
:)

[@saurabhpatel5545]

3:35 lol

[@ritikgupta4175]

sir , got r2_score =99.7

[@heaven-aman5946]

Congratulations overfitting

[@kishankalariya2485]

Sabse hard topic laga

[@shivoham5939]

i suggest you to watch stats quest regression tree

[@core4032]

Thanks sir
:)