Hi Madam, Your explanation is really good, I have one question at 9th Mins, You selected age example of 30, 30 to 40 & > 40 How can we decide this in the large sample... is there any formula behind it...or are we selecting randomly.... If yes... How can we depend on that random Number. I will be waiting for your response Thanks in Advance
Maam, In the last example ( video time 21:20) why are you taking Outlook attribute as a root node and left other attributes as internal node. Please reply.
Agar is k notes cheen le to ek min bhi na padha paye... As being a professor of IIT at least you should have enough knowledge so that you can teach without notes.
Sab kuch yaad rakhna knowledge nai hota hai bhai....Cheezo ko samajhna hota hai. And ma'am is sharing her knowledge on an open platform...so more respect is expected.
![Gunna - back in the a [Official Video]](http://i.ytimg.com/vi/oBrbejOHjLw/mqdefault.jpg)
How great our teachers are .. the more the knowledge the more the humbleness ... May God Bless you
Awesome explanation , The basic reason performing the DT , i got know from your Lecture ,other tutorials just give an example Thanks a Lot .
Thank you mam for teaching future ML practitioners and innovators
super explanation mam, Thank you so much.
Super Explaination Mam. Thankyou so much.
Thank you. Your videos changed my life literally 🥰
What a sweat lecturer you are. Thanks for your class.
Is this the next video after mon01lec05?
Hi Madam, Your explanation is really good,
I have one question at 9th Mins, You selected age example of 30, 30 to 40 & > 40
How can we decide this in the large sample... is there any formula behind it...or are we selecting randomly.... If yes... How can we depend on that random Number.
I will be waiting for your response
Thanks in Advance
You have to analyse the data. So that there are less number of ranges /categories with most information
Maam, In the last example ( video time 21:20) why are you taking Outlook attribute as a root node and left other attributes as internal node.
Please reply.
Mukesh Rajput Choosing an attribute is based up reduced entropies of features.
It has been selected as a root node because it has maximum information gain. Please check out the 2nd lecture of decision tree.
The algorithm has decided the root node based entropy value
where are the videos for Part A? This one only has Part B
There is mistake in subtitles: not "bullion", but "boolean" function.
excelent mam i wanna bow before you
What is the term for DECISION TREE LEARNING METHOD THAT CREATE MULTIPLE TREE.
Random Forest? 😄
Agar is k notes cheen le to ek min bhi na padha paye... As being a professor of IIT at least you should have enough knowledge so that you can teach without notes.
She did her PhD from standford university
apne baap se bol aake padha de phir
@@jyotbamania2112 Wow ! That says a lot about her stature.
Sab kuch yaad rakhna knowledge nai hota hai bhai....Cheezo ko samajhna hota hai. And ma'am is sharing her knowledge on an open platform...so more respect is expected.
Immature comment