Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2

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The explanation is great!
Why is it used?
1. ROC & AUC - Plotted between TPR & FPR, helps in - visualization & explanation & selection of a required threshold for the model!
What is ROC & AUC?
2. ROC - (Receiver Operating Characteristic curve) that you have drawn & AUC is the - (Area under the curve).
How does the curve look like?
3. AUC should be greater than the 0.5 line drawn, which indicates a better model.
🙇‍♂️🙇‍♂️🙇‍♂️

skviknesh

This channel is a gold mine. Thank you for your knowledge Krish.

LIMLIMLIM

This guy is definitely one of the best teacher available on YouTube
Simple but effective explaination
Lots of love for you Sir

suhaillone

I swear to God man, I learn more from you than my professors at school... you're saving my assignments

hassamdaudi

Bro, You are a gem. I mean not a single unnecessary word, everything is explained clearly and concisely. Many many thanks brother <3

borhanmukto

really ur communication ur voice and the way u explain it stole my heart rocking broooo

KiranKumar-bblr

Sometimes, I check this, that and then just search if you have made a video on the topic. No one can just simply explain better. You are an AVENGER.

mandeepsinghnegi

you're a true supervisor for supervised learning! 🌷

smiling_madly

Thanks krish.My doubts about ROC ad AUC are now clear.

sandipansarkar

Hi I couldn't find anywhere part 3 - performance metrics for classification problem part 3 ( you said in the first one there are 3 parts I only found 2).By the eay, I became a memeber more than half a year ago to support your work, because you are an excelent lecturer and you helped me a lot.

hilaav

Hey Krish, you are amazing! You explain topics clearly. So, everybody can understand it!

ayberkctis

great explanation video..anyone confused or overwhelmed about how much to study and from which channel to study...simply follow krish naik playlist from start to

athanikarammy

Krish, please make a video on "implementing all the Metrics For Classification Problem in ML by taking improper data set" as you mentioned in one of the videos of ML playlist (#1:05 minute of Tutorial 34 of Complete ML playlist)

syedyunus

SIr, it really helped me a lot. You really explained the concept in depth which makes it easy to get understand. thank you sir for this explanation..❤

venturousbuddies

Sir people like you should be admired ...big fan hope we meet one day

mohammadarif

I just hit the jackpot with this channel, thanks alot

firasfakih

Hats off Krish..u r so deep in knowledge

yashodhansatellite

Best explanation on the internet. Thanks Krish!

chaytanyakumar

After reading about roc and auc, your example calculating manually the values was perfect to finally understand this topic. Thank you!

guillermotorres

8:20 here I finally understand how to read the ROC curve. You really are great

adiflorense

Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2

Tutorial 41-Performance Metrics(ROC,AUC Curve) For Classification Problem In Machine Learning Part 2

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