THISSSSS!! GA must be mourning your departure. You are an incredible instructor and are very skilled at making complex material reachable to a wide audience. I see why this is the most popular video in your channel. I wish you great success in your Data School venture.
after 10 minutes of scratching my head looking at a dozen unlabeled lecture slides, I found this video. Thanks a lot for the clear explanation! I also now understand why an AUROCC of 0 would be a horrible / "excellent but mislabeled" test
Excellent work! Thanks very much Kevin, your video explaining ROC and AUC is the most intuitive one I have ever seen. Before watching this, it was still a little confusing for me , now I have a clear understanding of ROC and AUC.
Thank you so much for this video. Your logical, cumulative explanation and clear visuals have made the rationale for using ROC curves and AUC far easier to understand. I'll be subscribing to your channel immediately!
+Aayush Rampal You're very welcome! I created the video because my data science students were having a hard time with this concept, so I wanted to share my lesson with others :)
hot dawg, man, why do people in this field overcomplicate things so damn much. here is an accessible, free, easy to understand without sacrificing the innate complexity of the method message. Thank you, Data School crew!
Went through a couple of videos, this by far is the best explanation with the most apt visualization to support it. Bookmarking it as a reference material for the future in case I get muddled up(which I'm pretty sure I will)
Schrödinger (a large company develops software for drug discovery) linked this to one of their course material's additional resources so I went and watched this. No wonder they had this video there, as the subject was really well explained on the video
Awesome video, I searched many times on Google and finally your video is the best one. May I have a question, in 9:45, "the blue distribution would be nine times larger than the red distribution", however, in the probability theory, the area of one distribution is 1, so I don't think the blue distribution would be nine times larger than the red distribution.
Thanks for the great video. Could you please elaborate on the comment made at 11:31, namely that AUC gives the probability that a classifier will rank a randomly chosen positive observation higher than a randomly chosen negative observation. Doesn't how a classifier classifies depend on the threshold while the AUC is a way of summarizing how the classifier performs across different values of threshold?
It's hard to explain briefly, but the key is that I'm talking about ranking, and rank has nothing to do with the chosen value of the threshold. Does that help?
excellent explanation, the best that I have seen so far.
Thank you!
Indeed, agreed 100% with ed lee, definitely the best I explanation I have seen, much appreciated
You're very welcome!
I was about to type the same comment! Amazing explanation! Thank you for your contribution!
100% agree!!! thanks for the video
THIS IS THE BEST EXPLANATION OF ROC-AUC ON RUclips!
Thank you! 🙏
Likely the best explanation I've seen on ROC & AUC curves. Succinct yet thorough. The visualizations were extremely helpful. Nicely done.
Thank you so much for your kind and thoughtful comment! 🙏
I was searching in the net for videos and reading articles everywhere, but this is "The Best" Explanation I've found. Great work!
Thank you!
I have never seen an explanation of ROC-AUC better than this...thank you so much
Thank you so much! 🙏
I need to watch this a few more times to understand how it applies to my use-case, but this is a great overall explanation. Thank you for this!
You're welcome!
"If you can't explain it simply, you don't understand it well enough". YOU KILLED IT BRO! VERY WELL EXPLAINED!
Thanks so much! I'm so glad the video was helpful to you!
yes very good explanation indeed, I understood everything even though I'm high as a kite 😂😂😂
THISSSSS!! GA must be mourning your departure. You are an incredible instructor and are very skilled at making complex material reachable to a wide audience. I see why this is the most popular video in your channel. I wish you great success in your Data School venture.
Wow! Thank you so much for your very kind comment, I really appreciate it! :)
after 10 minutes of scratching my head looking at a dozen unlabeled lecture slides, I found this video. Thanks a lot for the clear explanation!
I also now understand why an AUROCC of 0 would be a horrible / "excellent but mislabeled" test
+phector2004 You're very welcome, glad to hear the video was helpful to you!
This is the best video on ROC and AUC that I have seen on RUclips. Great work Data School!
Awesome! Thanks for your kind comment :)
That's the best explanation in very simple words. Wow, man I wish the rest of the teachers in the whole world
could be like you.
Thank you so much for your very kind comment!
Excellent work! Thanks very much Kevin, your video explaining ROC and AUC is the most intuitive one I have ever seen. Before watching this, it was still a little confusing for me , now I have a clear understanding of ROC and AUC.
Great to hear! :)
This is the best mental model to explain ROC/AUC I seen so far, thanks a lot!
You're welcome!
undoubtedly one of the best explanation of ROC curve!!
Thanks very much! :)
amazing explanation the amount of information you fit into 14 minutes is magical.
Wow! Thank you so much for your kind words! :)
I am a Professor CSE from Annamalai University. The explanations given are very much appreciable. God bless you for ever your service with growth.
You're very welcome!
Thank you so much for this video. Your logical, cumulative explanation and clear visuals have made the rationale for using ROC curves and AUC far easier to understand. I'll be subscribing to your channel immediately!
Wow, thanks for your very kind comment, and for subscribing! Glad the video was helpful to you :)
The BEST explanation on this topic PERIOD.
Thank you so much!
A crisp and clear explanation, Thank you very much.
You're welcome!
I could have never understood this concept without this video!!!!!!!thanks a lot!
+Aayush Rampal You're very welcome! I created the video because my data science students were having a hard time with this concept, so I wanted to share my lesson with others :)
I always had a problem with understanding ROC, but for the first time I understood them flawlessly.
Thank you very much for this excellent video.
+Abdelrahman Eldesokey You're very welcome, thanks so much for the nice comment!
This is extraordinarily well explained. You're setting the bar really high here. I salute you.
Thank you so much for your kind comment!
Excellent content. This is by far the most concise, clear explanation I have found yet. Thanks!
Thank you!
hot dawg, man, why do people in this field overcomplicate things so damn much. here is an accessible, free, easy to understand without sacrificing the innate complexity of the method message. Thank you, Data School crew!
Thanks very much for your kind words! Glad to hear the videos have been helpful to you!
Awesome video!!! Covered some important points which are not covered by other videos on AUC-ROC.
Thank you!
great visualisation and explanation, made everything so much easier to understand
Awesome! Glad it was helpful to you!
What an amazing way to explain these concepts
even if some years are passed by, one of the best explanation around
Thanks very much for your kind words!
Best explanation I have seen so far .. Amazing .. pls keep going
Thank you!
This was a pretty amazing explanation of both ROC & AUC. This visual complemented the content and easily comprehensible to the listeners. Great Job
Ramasubramaniyan A Thanks for your generous compliment! Much appreciated :)
One of the best explanations of ROC and AUC. Many thanks!
Thank you!
This is a great example of 'how to teach'!! Kudos!
Thanks!
A very detailed and comprehensive explanation. Thank you.
You're welcome!
As usual, your each video is a savior, Mark. Excellent explaination
Thanks, Payal!
Been using auc-roc blindly so far - thank you for breaking it down so simply!!
You're very welcome!
Great explanation! I've been struggeling with these for some time now. Apperantly, all it took was a good visualisation! Thanks a lot!
You're welcome!
finally understood ROC. thank you
You're welcome!
Very good explanation. The best one I have seen so far.
Thanks so much for your kind words!
Usually, whenever I need goog understanding on any data science concept/statics releated topics, I search in this channel.
Thanks!
This is what they call as "Beautiful"
No unneccesary stuff... pure content
Thanks!
Great explanation, thank you so much!
Good speed, clear language and nice visualization.
Subscribed.
Thank you!
I am amazed by how you explain this subject so easily. Thanks a lot, it helped me very much.
Jose Paulo Henrique de Melo Fernandes Awesome to hear! Thanks for your comment :)
Went through a couple of videos, this by far is the best explanation with the most apt visualization to support it. Bookmarking it as a reference material for the future in case I get muddled up(which I'm pretty sure I will)
Great to hear! :)
Thanks for this explanation. Easy to comprehend. Best I have seen
Excellent! Thanks so much for your kind comment!
Excellent video. You nailed the essential components that were missing elsewhere. Subscribed and liked.
Awesome! Glad it was helpful to you :)
Excellent! The best on RUclips.
Thank you!
I've been trying hard to understand this metric. Thank god I found your tutorial.
Glad to hear I could be helpful! :)
Just fabulous - crystal clear explanation to something I had never really understood. Thank you!
Wow, thanks for your kind words! You are very welcome!
best explanation is far! it helped me understand the concept clearly. the visuals definitely added to the explanation. Thanks so much
You're very welcome! Thanks so much for your kind comments!
Nice job. Very well explained!
Thanks!
i just want to say thanks, thanks alot for keeping the explanation at its simplest. Keep up the good work :)
You're very welcome! Glad it was helpful to you :)
Best ROC/AUC tutorial ever!
+donkeyenvious Wow, thank you!
Really great video! I didn't really get the importance of ROC/AUC until I watch this video :-)
Thanks!
Excellent One. Just awesome. The best part is the visualization and the simple explanation
Thank you! I'm glad it was helpful to you!
Best explanation I've seen for this topic. Many thanks!
Thanks for your kind words!
Sometimes "less is better".
Crystal clear.. thanks :)
You're very welcome!
Great explanation. Thanks. People like u make the world a better place
+Mohamed Ghoneim Wow, thank you! I'm glad it was helpful to you!
A simple and fantastic explanation!
Thanks! :)
Schrödinger (a large company develops software for drug discovery) linked this to one of their course material's additional resources so I went and watched this. No wonder they had this video there, as the subject was really well explained on the video
That's great to hear, thanks for your kind comment!
Many thanks for this excellent video. You have a great gift for lucidly explaining complex concepts
Thank you so much! 🙌
Such a nice explanation,the best tht i've seen so far, this is what i hv been searching for
Awesome! Thanks for your kind words!
Great explanation, and wow sound exactly like Jim Rohn, one of my favorite motivational speaker.
Thanks!
Super stuff. ROC finally explained the way it should be.
+kumtomtum Thanks, I appreciate the compliment!
Absolutely amazing and intuitive explanation. Thanks a lot
Glad you liked it!
I've been for an explanation like this one for months! Thank you!!
You're very welcome!
Thanks for the wonderful explanation. I could not have been more simple, yet correct.
You're welcome!
Excellent! I am addicted to watching your vids. Thank you for the amazing work! Could you make some vids on using Tensorflow please? Cheers!
Thanks for your suggestion, and for your kind words! 👍
This explanation provides aesthetic pleasure to me
Thanks! :)
Perfect explanation which helps to remember this concept very well .
Thanks!
Thank you. I now understand, finally.
You’re welcome!
Clear explanation of the tough concepts! Thank you!
You're very welcome!
Very good and precise explanation. Thanks for creating the video.
You're very welcome!
So clear and easy to understand. Thank you
You're very welcome!
Detailed, simplisticT, and with great scenarios. Thank you very much for this!!!
You're very welcome! Glad to hear it was helpful to you!
Very clear and easy to understand! Thanks!
You're welcome!
Very nice explanation of the ROC curve !!
Thank you!
What the heck?! That was an awesome video, beautifully put!
Ha! Thank you :)
Besides this paper of Tom Fawcett is one of my favorite @@dataschool .
Very nice practical example of the roc, let me a clear idea of how I can check my classifier performance, thank you!
+Alex B. You're very welcome!
you are a legend, brother!
Thank you!
better than my professor's explain, awesome
Ha! Thanks :)
This is a very detailed and useful tutorial, thank you.
You're welcome!
Very good explanation!
Thank you!
Beautifully Explained :) Freaking awesome.
U deserve to get paid for this.
Thank you so much 😀
Thank you kind sir. U come to aid during dark times.
You're very welcome! :)
Nice way to explain ROC. Thanks very much :)
+Andika Yudha Utomo You're very welcome!
Very nice explanation and visualization. Thank you.
You're welcome!
Thank you so much. Truly. You are so appreciated.
🙏
Awesome video, I searched many times on Google and finally your video is the best one. May I have a question, in 9:45, "the blue distribution would be nine times larger than the red distribution", however, in the probability theory, the area of one distribution is 1, so I don't think the blue distribution would be nine times larger than the red distribution.
Glad you like the video! You're right, I'm using the word "distribution" in a different way.
Just to confirm. At 7:09, the 235 and 125 used as numerators were an estimate. If not, how to you generate those values?
+Karim Nasser That's correct, those were estimates only.
Awesome video! Very clear and concise. Thanks so much.
The Poet You're quite welcome! Thanks for your kind words.
amazing visualization and explanation!
Thanks!
Excellent explanation!! Very helpful, thank you!
You are very welcome!
very good and concise presentation!
מיכאל דימשיץ Thanks, I'm glad you like it!
finally understand AUC and ROC, excellent!
Great to hear!
Clear and on point explanation.
Thanks!
Thanks for the great video. Could you please elaborate on the comment made at 11:31, namely that AUC gives the probability that a classifier will rank a randomly chosen positive observation higher than a randomly chosen negative observation. Doesn't how a classifier classifies depend on the threshold while the AUC is a way of summarizing how the classifier performs across different values of threshold?
It's hard to explain briefly, but the key is that I'm talking about ranking, and rank has nothing to do with the chosen value of the threshold. Does that help?
You sir deserve a HUGE thank you.. you're a lifesaver
That's so nice of you to say!
very, very nicely done! also thanks for the paper!
You're very welcome!
This explanation is so good! I bookmarked this video :)
Thanks! :)
Thank you Kevin. Great video.
You're very welcome! Glad you liked it.