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

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  • เผยแพร่เมื่อ 22 ธ.ค. 2024

ความคิดเห็น • 186

  • @LIMLIMLIM111
    @LIMLIMLIM111 4 ปีที่แล้ว +104

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

  • @suhaillone831
    @suhaillone831 3 ปีที่แล้ว +13

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

  • @skviknesh
    @skviknesh 4 ปีที่แล้ว +17

    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.
    🙇‍♂️🙇‍♂️🙇‍♂️

  • @hassamdaudi
    @hassamdaudi 2 ปีที่แล้ว +11

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

    • @DappuDon
      @DappuDon 9 หลายเดือนก่อน

      In which school we are teaching ML?

  • @borhanmukto7770
    @borhanmukto7770 ปีที่แล้ว +3

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

  • @KiranKumar-bb8lr
    @KiranKumar-bb8lr 2 ปีที่แล้ว

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

  • @mandeepsinghnegi1931
    @mandeepsinghnegi1931 3 ปีที่แล้ว

    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.

  • @sandipansarkar9211
    @sandipansarkar9211 4 ปีที่แล้ว +1

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

  • @smiling_madly596
    @smiling_madly596 4 ปีที่แล้ว +5

    you're a true supervisor for supervised learning! 🌷

  • @athanikarammy7476
    @athanikarammy7476 3 ปีที่แล้ว

    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 end.....

  • @lumar_music
    @lumar_music 4 ปีที่แล้ว +39

    Please consider using manual focus and iso :D

  • @ayberkctis
    @ayberkctis 3 ปีที่แล้ว +3

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

  • @yashodhansatellite1
    @yashodhansatellite1 4 ปีที่แล้ว +2

    Hats off Krish..u r so deep in knowledge

  • @hilaav7449
    @hilaav7449 3 ปีที่แล้ว +1

    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.

  • @chaytanyakumar8939
    @chaytanyakumar8939 2 ปีที่แล้ว

    Best explanation on the internet. Thanks Krish!

  • @ayushijonwal9209
    @ayushijonwal9209 5 หลายเดือนก่อน

    Very clear and crisp explanation, great job👏

  • @guillermotorres4988
    @guillermotorres4988 3 ปีที่แล้ว

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

  • @firasfakih3050
    @firasfakih3050 3 ปีที่แล้ว +1

    I just hit the jackpot with this channel, thanks alot

  • @agenthitman7564
    @agenthitman7564 ปีที่แล้ว

    Finally I have understand ROC....Thank YOu Sir

  • @syedyunus4204
    @syedyunus4204 4 ปีที่แล้ว +8

    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)

  • @adiflorense1477
    @adiflorense1477 3 ปีที่แล้ว +1

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

  • @mohammadarif8057
    @mohammadarif8057 4 ปีที่แล้ว

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

  • @230489shraddha
    @230489shraddha 3 ปีที่แล้ว

    Krish you explain data science concepts so clearly that I have become fan of your's !!! thanks a ton man!!!

  • @souvikmaitra6653
    @souvikmaitra6653 4 ปีที่แล้ว +1

    awsum explaination...ALL THE BEST for all your upcoming videos #Krish.

  • @teamannonymous163
    @teamannonymous163 3 ปีที่แล้ว

    totally clear .. you way of explanations are really very amazing.

  • @xyzaex
    @xyzaex 4 ปีที่แล้ว

    Brilliant. You are officially Sensei.

  • @lavanyathippineni6341
    @lavanyathippineni6341 3 ปีที่แล้ว +1

    Superb explanation👌👏👏👏....Waiting for part-3. Please upload it as possible as sir

  • @narenderbansal5741
    @narenderbansal5741 4 ปีที่แล้ว +1

    Very nicely explained. Thanks for sharing.

  • @MrYoonyan
    @MrYoonyan 3 ปีที่แล้ว

    The best explanation ever seen, thank you

  • @abhishekranjan2617
    @abhishekranjan2617 3 ปีที่แล้ว +1

    Awesome video sir.
    I love it😍😍🥰🥰😘😊😊🙏🙏🙏🙏🙏👌👌👌👌

  • @sahithim9278
    @sahithim9278 4 ปีที่แล้ว +3

    for the threshold value of y^=0.4 and y^=0.6 , tpr and fpr values is same i.e.,(0.5,0.5) and for y^=0.8 is (0,0.5). Now the graph will be different and AUC might be less than 0.5.

  • @adiflorense1477
    @adiflorense1477 3 ปีที่แล้ว +1

    0:52 how to determine the threshold. can we set the threshold ourselves?

  • @kranthikumar7635
    @kranthikumar7635 4 ปีที่แล้ว +1

    really awesome explanation....

  • @agnelraju718
    @agnelraju718 3 ปีที่แล้ว

    superb explanation loved each bit😍😍

  • @sumitnaina
    @sumitnaina 3 ปีที่แล้ว

    You explained it so nicely and make me understand the roc and auc concept so easily. Thanks a lot krish

  • @chandrusaekarb3445
    @chandrusaekarb3445 4 ปีที่แล้ว +1

    Nice Video and clear explanation. Thanks a ton ! .. Please do post part-3 of the metrics soon....

  • @avinashmandora8745
    @avinashmandora8745 ปีที่แล้ว

    What an informative video. Really amazing!

  • @fortask5897
    @fortask5897 2 ปีที่แล้ว

    Lovely Explanation.

  • @rishigupta2342
    @rishigupta2342 2 ปีที่แล้ว

    Brilliant explanation. Please make part 3 of this video.

  • @tengliyuan1988
    @tengliyuan1988 4 ปีที่แล้ว

    Krish I really appreciate your effort in sharing your knowledge. Thanks

  • @happytorev466
    @happytorev466 4 ปีที่แล้ว +1

    Thank you for this video. Eagerly waiting for part 3.

  • @saikatkar547
    @saikatkar547 2 ปีที่แล้ว

    Very nicely presented ...clearly understood . Thank you sir

  • @mr.top5636
    @mr.top5636 3 ปีที่แล้ว

    Your explanation is just amazing go ahead man

  • @chubiandchuba4804
    @chubiandchuba4804 4 ปีที่แล้ว +1

    Hi Krish you are really superb... Excellent knowledge, well explained

  • @ianmutuma6564
    @ianmutuma6564 4 ปีที่แล้ว

    Thanks Krish. This saved me a couple of hours

  • @amoldeshmukh8244
    @amoldeshmukh8244 4 ปีที่แล้ว +5

    Hey Krish , Did you uploaded Part-3 of this video (i.e. Performance Metrics for Classification problem) ?

  • @ankita684
    @ankita684 4 ปีที่แล้ว +2

    Hi...can you share the link for part 3 of the performance metric video.
    Also, can you share any real life example when domain expertise would want threshold to be say 0, 0.6.?

  • @jagadeeshabburi570
    @jagadeeshabburi570 4 ปีที่แล้ว

    Maza agaya bhai dekeke. Subscribed. The thing what I felt lacking was. More explainanation

  • @hemrajbhatt1034
    @hemrajbhatt1034 4 ปีที่แล้ว

    Thanks a lot sir. I was seriously waiting since your last video on performance metrics.

  • @sampsonagudze8674
    @sampsonagudze8674 4 ปีที่แล้ว +1

    Fantastic!

  • @ozcanf6680
    @ozcanf6680 3 ปีที่แล้ว

    Great video, thank you Krish

  • @kaustubhshete6250
    @kaustubhshete6250 4 ปีที่แล้ว

    Awesome Work Sir !!

  • @iamramanr4s
    @iamramanr4s 2 ปีที่แล้ว

    In the case of binary classifier that outputs 0 and 1 labels how can we calculate auc score and roc curve

  • @myGiG-09
    @myGiG-09 ปีที่แล้ว

    Awesome lecture

  • @dordonduty2918
    @dordonduty2918 3 ปีที่แล้ว

    very short and srisp, i love it

  • @fancy4926
    @fancy4926 4 ปีที่แล้ว +2

    Krish, at the end of this video, you said: "if they focus on both TPR and FPR, we can also choose TH(0.4) at that plot". But in real ROC there are always a lot of inflection points like TH(0.4), then which inflection point should we choose?

  • @asawanted
    @asawanted 3 ปีที่แล้ว

    So comparing the Andrew Ng video, the true positive rate is same as recall? and the false positive rate is same as precision?

  • @sonalighadage6253
    @sonalighadage6253 4 ปีที่แล้ว

    very nice explanation

  • @avisii8928
    @avisii8928 9 หลายเดือนก่อน

    hello sir, i am working on my final year project, Resume classification and ranking system using knn and cosine similarity, the roc auc curve for all my class label came 0.5, what should i do?

  • @pranjan85
    @pranjan85 4 ปีที่แล้ว +4

    Hi Krish, Can you please upload Part-3 so that everything can be understood

  • @tannurohela6192
    @tannurohela6192 2 ปีที่แล้ว

    Great explanation but I didn't get how to take the threshold values , this is , the values we have taken to predict and draw ROC. Can we select them randomly or is there a way?

  • @ExploreElectronics
    @ExploreElectronics 3 ปีที่แล้ว

    Understood ROC. can any one suggest me video on "(CMC)Cumulative Match Score Curve"

  • @neelroy4153
    @neelroy4153 2 ปีที่แล้ว

    Hi Krish, how did you come up with original y hat?

  • @megalaramu
    @megalaramu 4 ปีที่แล้ว +3

    Hi Krish, Awesome explanation. Thanks a ton. Could you please help us by giving an example (Part-3) for all the performance metric in python.

    • @kanakkumar5261
      @kanakkumar5261 4 ปีที่แล้ว

      Hi Krish, awesome teaching skills... please upload all parameters in python programming language take an example like iris data

  • @louerleseigneur4532
    @louerleseigneur4532 3 ปีที่แล้ว

    Thanks Krish

  • @narenderbansal5741
    @narenderbansal5741 4 ปีที่แล้ว +1

    Hi Krish, Suppose i want to set the threshold at .75. then how i can do this in python code. is there any parameter in ruc_curve method or have to do it by using logic/code.

  • @itwind9912
    @itwind9912 ปีที่แล้ว

    Can we use AUC-ROC for multiclafication problem?

  • @binnypatel7061
    @binnypatel7061 4 ปีที่แล้ว

    Keep up the good work.....Great explanation!

  • @kaisersayed9974
    @kaisersayed9974 4 ปีที่แล้ว +2

    Sir please make videos on web scrapping for beginners.. please sir and I am anabel to get the link of AQI website which you have shown in the video ....but please make more videos on web scrapping..

  • @Su.arya31
    @Su.arya31 10 หลายเดือนก่อน

    Hello sir , just a doubt need your help , I have a sample value, a control value and also a AUC value … I just want to plot 2*2 confusion matrix table… can you please help me

  • @hemantdas9546
    @hemantdas9546 4 ปีที่แล้ว

    Super Sir. Very clear

  • @tuannguyen4802
    @tuannguyen4802 3 ปีที่แล้ว

    Amazing explanation

  • @Amd107
    @Amd107 2 ปีที่แล้ว

    One construtive feedback: please lock your phone's focus so that it doesn't go haywire like at 1:47

  • @krishnab6444
    @krishnab6444 2 ปีที่แล้ว

    perfectly explained

  • @shaz-z506
    @shaz-z506 4 ปีที่แล้ว +1

    Good video Krish, could you please create a video on Cohen-Kappa score.

  • @chitrashivraj8403
    @chitrashivraj8403 4 ปีที่แล้ว +1

    You are awesome krish. It takes so much effort to reach here. Brilliant :D

  • @adityagandhamal2351
    @adityagandhamal2351 4 ปีที่แล้ว

    Thank you sir....It was very helpful.

  • @pshubhamoy21
    @pshubhamoy21 3 ปีที่แล้ว

    nicely explained

  • @anujlahoty8022
    @anujlahoty8022 4 ปีที่แล้ว

    Awesome video.

  • @abhishek-shrm
    @abhishek-shrm 4 ปีที่แล้ว

    Great video Sir.

  • @sanketannadate4407
    @sanketannadate4407 6 หลายเดือนก่อน

    it really helped thnx

  • @sohinimitra7559
    @sohinimitra7559 4 ปีที่แล้ว

    Hi Krish, your videos are very informative and helpful. I saw your video where you explained ROC-AUC based on thresholds in Logistic Regression. What is the intuition about thresholds for other classification models? For example, a decision tree will split based on feature value to determine the class, how is ROC constructed here? Similarly, for other classification algorithms, how is ROC constructed?

  • @avinashreddy5779
    @avinashreddy5779 2 ปีที่แล้ว

    thanks for your knowledge Krish sir,
    I am new to date science ROC used to evaluate the logistic regression only or do we have any uses can anyone help with this

  • @laxmimansukhani1825
    @laxmimansukhani1825 4 หลายเดือนก่อน

    awesome !!

  • @mohsin10185
    @mohsin10185 3 ปีที่แล้ว

    Excellent

  • @sushilchauhan2586
    @sushilchauhan2586 4 ปีที่แล้ว +2

    CAN YOU PLS EXPLAIN MULTICOLINEARITY AND HOW TO AVOID IT ? PLS or PERTUBATION TEST

  • @sibamarcel9428
    @sibamarcel9428 4 ปีที่แล้ว

    You have great knowleg...Thanks a lot

  • @ravinch7973
    @ravinch7973 2 ปีที่แล้ว

    Explain about epoch and its graphs with accuracy, Precision, Recall, f1Score. Also show in python or matlib how to draw

  • @dheerajkumark2268
    @dheerajkumark2268 4 ปีที่แล้ว +1

    Sir can you plz make videos on statsmodal and scipy library

  • @amitbudhiraja7498
    @amitbudhiraja7498 2 ปีที่แล้ว

    Can someone tell that as the sir said we have to see all these different metrics when we have an unbalanced dataset if we have balanced datasets then only accuracy is enough?

    • @redroom07
      @redroom07 4 วันที่ผ่านมา

      You can use precision & recall metrics,

  • @shaunakchadha4204
    @shaunakchadha4204 3 ปีที่แล้ว

    Krish sir...... Hrithik Roshan ke bajaae aapko le rahe hain agli Krish Movie mein ??? Hero ho aap sir

  • @gupta89ankita
    @gupta89ankita ปีที่แล้ว

    sir can you explain roc auc in context to drought stress detection

  • @saivenkat8813
    @saivenkat8813 3 ปีที่แล้ว

    hi krish in the previous lecture u said fpr =fp/p =fp/tp+fn now in this video it is fp/fp+tn which one is correct

  • @gangeshwarinetam413
    @gangeshwarinetam413 2 ปีที่แล้ว +1

    what is the meaning of threshold value

  • @godse54
    @godse54 3 ปีที่แล้ว

    krish please make part 3 and also list some performance matrix for multiclass classification.

  • @nikhilshakkarwar3733
    @nikhilshakkarwar3733 3 ปีที่แล้ว

    How to use ROC AUC for multi-class problem?

  • @tomasvonbischoffshau
    @tomasvonbischoffshau 2 ปีที่แล้ว

    Thanks! really.

  • @Devpatel-oi1er
    @Devpatel-oi1er 2 ปีที่แล้ว

    where is model building & deployment part of EDA project

  • @nareshkumar-dc7bq
    @nareshkumar-dc7bq 4 ปีที่แล้ว +4

    HI Krish, I really appreciate you can provide me the link to part 3 session of the performance matrix please.

  • @subhasrik1436
    @subhasrik1436 2 ปีที่แล้ว

    sir excellent ,plz explain eer from det curve