The quality of content is so good, I wonder why there are fewer views. But no worries you are doing a great job bro, keep it up and people will eventually find you.
Hi Rachit ..while training part my model perform well.when there is class distribution like 1:60% and 0:40%. But when i use test data set with different class distribution like 1:30% and 0:70% then it perform worse..why? ..
@@rachittoshniwal Thanks for reply Rachit🙏, Yes but I have already used stratified K fold cross validation technique tried with fold 3,4. Bt still performance is bad when i change distribution for test data.
@@tusgyu851 cross validation will give you a general sense of the data performance. Train test split will sometimes give you good performance, sometimes bad depending on what data ends up in the test set, which makes it unreliable
Rachit, the content of you channel is pure GOLD, thank you for sharing your knowledge, you are great!! However, I've got a small objection regarding the Variance threshold. Shouldn't we also check the mean of the column before we proceed with dropping a quasi-constant feature? For example, if we have variance = 0.0095, and a mean value of 0.003, can we still drop that feature? (lets say we have medical data) And question number 2 :) Which courses/books/youtubeChannes would you recommend for more intermediate level content like yours? Once again, a HUGE thank you
The word “namaste" in Sanskrit means “bowing to you". Muslims believe that one can bow/prostrate only to Allah. We don't bow down to any human. It's important to note that religious beliefs and practices can vary among individuals and communities.
The quality of content is so good, I wonder why there are fewer views. But no worries you are doing a great job bro, keep it up and people will eventually find you.
Thanks Ravi!
Thank you for the very clear explanation 🙂
Hi Rachit ..while training part my model perform well.when there is class distribution like 1:60% and 0:40%.
But when i use test data set with different class distribution like 1:30% and 0:70% then it perform worse..why? ..
can you please help me with this?
Different test sets would give you different results. So it's better to do cross validation, which provides a more holistic view of the data at hand
@@rachittoshniwal Thanks for reply Rachit🙏, Yes but I have already used stratified K fold cross validation technique tried with fold 3,4. Bt still performance is bad when i change distribution for test data.
Also my data set was right skewed and I also used log transformation for that.
@@tusgyu851 cross validation will give you a general sense of the data performance. Train test split will sometimes give you good performance, sometimes bad depending on what data ends up in the test set, which makes it unreliable
Rachit, the content of you channel is pure GOLD, thank you for sharing your knowledge, you are great!!
However, I've got a small objection regarding the Variance threshold. Shouldn't we also check the mean of the column before we proceed with dropping a quasi-constant feature?
For example, if we have variance = 0.0095, and a mean value of 0.003, can we still drop that feature? (lets say we have medical data)
And question number 2 :)
Which courses/books/youtubeChannes would you recommend for more intermediate level content like yours?
Once again, a HUGE thank you
Great video bro, can you add subtitle English?
Sorry bro, won't be able to do it
@@rachittoshniwal ok bro, but can you add automatic english subtitles on the next video
@@whyme6543 oh, I thought the automatic ones did appear. I'll look into it though, thanks!
@@rachittoshniwal thanks for your attention bro, but the automatic subtitles don't exist yet, thanks again bro
The word “namaste" in Sanskrit means “bowing to you". Muslims believe that one can bow/prostrate only to Allah. We don't bow down to any human. It's important to note that religious beliefs and practices can vary among individuals and communities.
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