Making sense of the confusion matrix

แชร์
ฝัง
  • เผยแพร่เมื่อ 11 พ.ย. 2024

ความคิดเห็น • 145

  • @echozero31
    @echozero31 2 ปีที่แล้ว +1

    Hands down, the best source for Confusion Matrix: Explained. If you are stuck, no matter how long you have been doing this for - I highly recommend you take a 35min break to watch Kevin's
    video. A+

    • @dataschool
      @dataschool  2 ปีที่แล้ว

      Thank you so much! 🙏

  • @ryan22351
    @ryan22351 5 ปีที่แล้ว +5

    Thanks Kev, inserting "predicted as" helps me remember it - false (predicted as) positive | false (predicted as) negative

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Glad that is helpful to you! :)

  • @OrcaChess
    @OrcaChess 6 ปีที่แล้ว +41

    Now the Confusion Matrix is less confusing to me! Appreciated it :)

    • @dataschool
      @dataschool  6 ปีที่แล้ว +2

      That's awesome! Thanks so much for watching :)

    • @OrcaChess
      @OrcaChess 6 ปีที่แล้ว

      @@dataschool Thanks for giving the world a good start into machine learning!

    • @dataschool
      @dataschool  6 ปีที่แล้ว +1

      You're very welcome! It's my pleasure.

    • @BeFourCM
      @BeFourCM 2 หลายเดือนก่อน

      ​@@OrcaChessoh hello fellow chess player, didn't expect to see you here.😂

  • @julieye2260
    @julieye2260 2 ปีที่แล้ว +2

    This is my favorite video of explaining what confusion matrix is. Thank you so much for your great work!

  • @gubben02
    @gubben02 6 ปีที่แล้ว +3

    Thanks for this video!
    I'm sure, I'm not the only one who appreciates what you do for the community.

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      You are very welcome! And, I'm happy to contribute to the community :)

  • @geekyprogrammer4831
    @geekyprogrammer4831 3 ปีที่แล้ว +1

    Truly the best video on Confusion Matrix!

  • @borjaatp501
    @borjaatp501 2 ปีที่แล้ว +1

    Thank you Kevin for your time to prepare, record and share the video. Now I have a better understanding about the Confusion matrix topic 😀

    • @dataschool
      @dataschool  2 ปีที่แล้ว

      Great to hear! You're welcome!

  • @haneeshhaneesh5105
    @haneeshhaneesh5105 5 ปีที่แล้ว +5

    This is the first video i have seen from data school, really impressed with the concept and explanation. I think i should not go back to check for another confusion matrix videos or tutorials. This is really helpful. Thanks

    • @dataschool
      @dataschool  4 ปีที่แล้ว

      Thanks so much for your kind words!

  • @dariuszspiewak5624
    @dariuszspiewak5624 2 ปีที่แล้ว +1

    Hi Kevin. This exposition of yours is a real gem. A splendid explanation. I think one of the best things you've done here is pairing the terms with the questions they should answer. This is truly helpful. I'd like to take this opportunity and recommend your course on ML to anyone that would like to dive into the field. I have taken it and come back to it regularly. Thank you so much for your effort and dedication to the subject. They are unmatched.

    • @dataschool
      @dataschool  2 ปีที่แล้ว

      Thank you so much, Dariusz! You are so kind and I really appreciate it! 🙏

  • @williamzheng5918
    @williamzheng5918 5 ปีที่แล้ว +2

    29:00: "Choice of metric depends on your business objective." I approve this message!

  • @manogyapulivendala2504
    @manogyapulivendala2504 5 ปีที่แล้ว +4

    Thank you for this amazing video and specially for inserting the words "predicted as". It helps us all remember!

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Awesome! Glad that tip was helpful to you 🙌

  • @ejkitchen
    @ejkitchen 3 ปีที่แล้ว

    Best video I have seen so far on all of the topics you covered. No wonder it's #1 in Google search.

  • @praveenchaubey7018
    @praveenchaubey7018 5 ปีที่แล้ว +2

    Thanks for helping with confusion matrix, i am a beginner in this field and your video helped me a lot to understand this.

  • @IbrahimOgunbiyi-s4x
    @IbrahimOgunbiyi-s4x ปีที่แล้ว +1

    This is really impactful Kevin. I gained a ton lot of information's.

    • @dataschool
      @dataschool  10 หลายเดือนก่อน

      Great to hear!

  • @skviknesh
    @skviknesh 5 ปีที่แล้ว +3

    Awesome Bro!!! Great Work! Appreciate your patience & detication in explaining something really confusing in depth- layman terms. Keep Rocking!!!

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Thanks very much for your kind words! I appreciate it 🙌

  • @eturkoz
    @eturkoz 5 ปีที่แล้ว

    Your explanations are really really great. You are the master of terminology and give fluent and concrete examples to clarify any subject you know about.

    • @dataschool
      @dataschool  5 ปีที่แล้ว +1

      Thanks so much!! :)

  • @mudolee
    @mudolee 4 ปีที่แล้ว +2

    this is it! it just saved me from many confusing posts so far.

  • @rbr951
    @rbr951 5 ปีที่แล้ว

    Hey Kevin, you are an awesome teacher. Not everyone is gifted like you are. Keep it up.

    • @dataschool
      @dataschool  4 ปีที่แล้ว

      Thanks very much for your kind words!

  • @chaimaelaissaoui6870
    @chaimaelaissaoui6870 ปีที่แล้ว +1

    wow videos like this make me understand that some people are just so much better at explaining things than others. Thank you so much for this wellput video. u saved my grades haha

    • @dataschool
      @dataschool  ปีที่แล้ว

      You're very welcome! Thanks for your kind comment!

  • @Digitabe
    @Digitabe 5 ปีที่แล้ว +1

    No more confusion! Thank you friend..

  • @Diamond_Hanz
    @Diamond_Hanz 2 ปีที่แล้ว +1

    Amazing Video!

  • @shaikayub8922
    @shaikayub8922 4 ปีที่แล้ว

    i really loved the way you explain the confusion matrix ,finally i am upto it ,much thanks for the video.

  • @stevemackay8082
    @stevemackay8082 5 ปีที่แล้ว +1

    Thank you so much Kevin for a brilliantly meticulous dissertation. C'est magnifique.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Awesome! Thanks so much for your kind words :)

  • @what594
    @what594 4 ปีที่แล้ว

    Amazing video... Really explained in detail with real examples.

  • @SayantanSenBony
    @SayantanSenBony 5 ปีที่แล้ว +2

    Great presentation,clear explanation :)

  • @lucassudo9857
    @lucassudo9857 6 ปีที่แล้ว +1

    Man, thank you for your TH-cam's channel. Your videos helps a lot.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Great to hear, thanks!

  • @reibalachandran4775
    @reibalachandran4775 4 ปีที่แล้ว

    Thanks a lot Kevin! Things just cleared up after I watch your video! Great work, please keep it up!

  • @preetisrivastava1624
    @preetisrivastava1624 ปีที่แล้ว +2

    Wow thanks for this wonderful and easy to understand approach towards this concept.....sir do you have any course also would love to join

    • @dataschool
      @dataschool  ปีที่แล้ว

      I do have offer courses! See here: courses.dataschool.io

  • @vivekagrw
    @vivekagrw 5 ปีที่แล้ว +1

    I have seen many of yours video...must say all of your are very helpful....👍

  • @dataschool
    @dataschool  6 ปีที่แล้ว

    Hi everyone! Join me for the Premiere of this 35-minute video on October 31 at 11:00 AM Eastern Time! I'll be hanging out here and answering your questions LIVE while we watch the video together :)

  • @saddamalikhanpathan8020
    @saddamalikhanpathan8020 5 ปีที่แล้ว +1

    now no confusion on confusion matrix.. thank You

  • @jaid7811
    @jaid7811 5 ปีที่แล้ว

    Actually, I love your teaching and your panda's course help me a lot....., I have a small suggestion for you especially in this one if you use the pen while your explanation, it might be easy to understand

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Thanks for your suggestion!

  • @satishchhatpar
    @satishchhatpar 3 ปีที่แล้ว

    Thank you. Very good explanation.

  • @floweast
    @floweast 5 ปีที่แล้ว

    the best video about this topic after watching several other video!!!

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      That's awesome to hear!

  • @nowhere5111
    @nowhere5111 4 ปีที่แล้ว +1

    Great video 👍👍

  • @saranyachimirala8351
    @saranyachimirala8351 4 ปีที่แล้ว +1

    This video was really helpful. But can you also explain what exactly base rate and test incidence are?

  • @knageswarareddy
    @knageswarareddy 3 ปีที่แล้ว

    Superb explanation

  • @gandtakwadi69
    @gandtakwadi69 6 ปีที่แล้ว +1

    Beard will suit you.Keep up the good work Kevin.Your videos help a lot...

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      Ha! Thanks Dean :) That's great to hear!

  • @special3070
    @special3070 2 ปีที่แล้ว

    thank you so much ,sir what reference you use i need to read in pls

  • @rohitbhosale8755
    @rohitbhosale8755 2 ปีที่แล้ว +1

    You ara a champion.

  • @pialatour3600
    @pialatour3600 3 ปีที่แล้ว +1

    Hey there, thank so much for this video! I was so confused with true and false positives and so on but you have clearly cleared my mind!
    But I have a problem:
    What do I do, if I don’t have any reference data to compare my classification with? I’m using SNAP for a random forest classification of Landsat images. I just have 2 classes: urban and non-urban
    I made training samples for these two classes and after my classification I made new training samples for a new class called urban-validation and another class called non-urban-validation. As I don’t have any other data than my self-made classification of the satellite image, I guess my training samples for the two validation classes would have an accuracy of 100 %.
    That’s why I don’t know if it’s even necessary to do a confusion matrix?
    But if I would still want to do a confusion matrix, which classes should I use?
    Do you or someone else have an idea what I should do? I would be so greatful!!
    Have a good day!

  • @yasmin_jsmn
    @yasmin_jsmn 3 ปีที่แล้ว

    Thank you, it's really helpful.

  • @dilipgawade9686
    @dilipgawade9686 6 ปีที่แล้ว

    Your videos are so much simple to understand. I have been trying to learn TensorFlow but do not find any good videos for beginner level and practical examples. Would it be possible for you to start Tensorflow session on your channel ?

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      Thanks so much for your kind words, and for your suggestion! I'll consider it for the future :)

  • @panagiotisgoulas8539
    @panagiotisgoulas8539 2 ปีที่แล้ว

    Kevin, do you have any example of out of sample data that I can measure the true values and not an estimate via my classification model?
    You mentioned so on 2:00 .
    Thanks

  • @goodman9585
    @goodman9585 3 ปีที่แล้ว +1

    How to calculate average precision and average recall?

  • @emmaekstrom5169
    @emmaekstrom5169 4 ปีที่แล้ว +1

    Hey great stuff! How can missclassification errors be calculated for multiple-case confusion matrixes? And what does it really mean?

  • @bevansmith3210
    @bevansmith3210 5 ปีที่แล้ว

    Thanks Kevin. How do we construct a confusion matrix if we use k-fold cross validation? I understand using a single train test split, but not sure how to do it with multiple cross validation. Thanks.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      I think you can accomplish this with cross_val_predict. Hope that helps!

  • @houyao2147
    @houyao2147 6 ปีที่แล้ว +1

    Excellent!

  • @DunedinNZ09
    @DunedinNZ09 5 ปีที่แล้ว +1

    Thank You! Awesome video! :D

  • @shahmainurrahman8510
    @shahmainurrahman8510 4 ปีที่แล้ว

    The number of predictions (n) depends on what??
    If we have 5000 test data, what will be the number of predictions(n) for confusion matrix?

  • @username42
    @username42 4 ปีที่แล้ว +1

    this is the literally the meaning of confusion :D

  • @Priya_dancelover
    @Priya_dancelover 2 ปีที่แล้ว

    Excellent

  • @adeogunpradel6631
    @adeogunpradel6631 4 ปีที่แล้ว +1

    Thank you!!!!!!

  • @nagnathsatav9978
    @nagnathsatav9978 4 ปีที่แล้ว

    Just awesome

  • @Uma7473
    @Uma7473 3 ปีที่แล้ว

    From classification rules can we derive at confusion matrix? is my question weird or wrong?

  • @vijaykumar-yq7sf
    @vijaykumar-yq7sf 6 ปีที่แล้ว

    great explanation. thank u

  • @muhammadnasrollahi1307
    @muhammadnasrollahi1307 4 ปีที่แล้ว

    Hi teacher
    At first, let me appreciate you for this awesome tutorial
    but here I have question.
    I've used classification app in Matlab and calculated the confusion matrix but I can't calculate some factors like Accuracy, Misclassification Rate, Precision, Recall and etc
    I'm wondering I you help me
    Thanks
    King regards
    Muhammad

  • @khafidakbar1103
    @khafidakbar1103 4 ปีที่แล้ว

    from that condition, how to calculate misclassification cost ?

  • @AvinashKunamneni
    @AvinashKunamneni 6 ปีที่แล้ว

    Hey can i apply the confusion matrix for the risk assessment of an e-learning website based on the key factors of participants, technology, information, infrastructure, technology ??

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      You can use the confusion matrix for any classification problem, regardless of the subject. Hope that helps!

    • @AvinashKunamneni
      @AvinashKunamneni 6 ปีที่แล้ว

      @@dataschool But I have a dataset with a classification of 5 how could i proceed with the confusion matrix?
      I'm a bit confused could u pls help me out ?

    • @mkumar4059
      @mkumar4059 6 ปีที่แล้ว

      @@@AvinashKunamneni ,Firstly choose one coloumn as your response, and corresponding to that response select best among other 4 columns (1 already chosen as response).Then You can use confusion on each.That's it.Keep learning.

    • @AvinashKunamneni
      @AvinashKunamneni 6 ปีที่แล้ว

      @@mkumar4059 sorry I didn't get you... I have the classifications as agree, strongly agree, neither agree nor disaggree, disaggree, strongly disagree for 20 questions for each factor mentioned in the above reply

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      Based on my understanding of your problem, it doesn't sound like a confusion matrix is the tool you are looking for. Good luck!

  • @awakenedspirit6397
    @awakenedspirit6397 3 ปีที่แล้ว

    Hello @Data School can you drop the slides of the tutorial

    • @dataschool
      @dataschool  3 ปีที่แล้ว

      There are no slides, but this is the main resource: www.dataschool.io/simple-guide-to-confusion-matrix-terminology/

  • @BwithGadgets
    @BwithGadgets 5 ปีที่แล้ว

    Hello Sir..in your video the Predicted class is shown on x axis but per wikipedia n some other experts the predicted class is on the y axis of the matrix. Plz let me knw if m correct.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      Right, there are different ways that the confusion matrix can be displayed. None of them is the "right" way. Hope that helps!

    • @Shripadsmail
      @Shripadsmail 5 ปีที่แล้ว

      Learning the confusion matrix with Actual classes on left side will be useful if you are using sklearn output

  • @ankitakushwah9121
    @ankitakushwah9121 5 ปีที่แล้ว

    Hii. can you please explain me how to calculate classification results on the basis of various attributes from multiple Reviews. if there is 5 clases and each classes includes various reviews. according to that reviews we find unique attributes and we have to find how many times that attribute is occur in the reviews. and also to find that the attribute is belong to which class.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      I'm sorry, I don't understand your question. Good luck!

  • @adityarajora7219
    @adityarajora7219 6 ปีที่แล้ว

    Love you bro!!!!

  • @mannankohli
    @mannankohli 5 ปีที่แล้ว

    hi there,
    i m working with election predictions. i have developed the model using 2018 election data-set and test it on 2013 and 2008 election data-set. now my question is that how to get the mean of all confusion matrix for three elections in one single model.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      I don't quite understand what you are trying to do, I'm sorry!

    • @Shripadsmail
      @Shripadsmail 5 ปีที่แล้ว

      Sum all the values from the three models and report.

    • @mannankohli
      @mannankohli 5 ปีที่แล้ว

      @@Shripadsmail thanks a lot
      But how to sum all the values of three different model
      Will u please elaborate with some examples

    • @Shripadsmail
      @Shripadsmail 5 ปีที่แล้ว

      @@mannankohli Ideally for one model, there will be one confusion matrix.
      If you have three models, three confusion matrix. That way we can compare these models. But if you want only one confusion matrix for some reason, may be you can treat these three models as one model and construct a confusion matrix (which is not advisable). If you are still not unclear you can email me.

  • @coxixx
    @coxixx 6 ปีที่แล้ว

    would you make a video about inverted index?

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      Are you referring to the inverted index data structure? Thanks for the request, but I'm not the right person to teach that subject... I'm sorry!

  • @leavedrakealone1801
    @leavedrakealone1801 5 ปีที่แล้ว

    Little confused here. First you said that the classifier predicted 'No' 55 times. Then you said that the classifier predicted 'No' 50 times which was the Actual value as well therefor its a True Negative. Does that mean it predicted No 50 times or 55 times?

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      It predicted "no" 55 times. 50 of those times it was a correct prediction (which is called a True Negative), and 5 of those times it was an incorrect prediction (which is called a False Negative). Hope that helps!

  • @faisalliaqat5735
    @faisalliaqat5735 3 ปีที่แล้ว

    Tell me how tu calculate matrix value. you are already written these value

    • @dataschool
      @dataschool  3 ปีที่แล้ว

      See here for how to do it in scikit-learn: th-cam.com/video/irHhDMbw3xo/w-d-xo.html

  • @NiranjanBallal
    @NiranjanBallal 4 ปีที่แล้ว +1

    You defined the equations and did not give the definition. For example, how exactly should we perceive Sensitivity or Precision?

    • @dataschool
      @dataschool  4 ปีที่แล้ว

      Does this help? www.dataschool.io/simple-guide-to-confusion-matrix-terminology/

  • @ziyadmoraished6097
    @ziyadmoraished6097 4 ปีที่แล้ว

    Thanks a lot for explaining it !!
    ConfusionMat.com
    is a website that explains it in an interactive way :)

    • @dataschool
      @dataschool  4 ปีที่แล้ว

      Thanks for sharing!

  • @ChandraveshChaudhari
    @ChandraveshChaudhari 5 ปีที่แล้ว

    thanks man, if anyone want to know about Mnist confusion matrix go to 24:42

  • @goldenmonkey9085
    @goldenmonkey9085 6 ปีที่แล้ว

    I come from China, and start to learn python for half year. can you teach me visualization in matplotlib or seaborn ?
    I can't find a very perfect videos about visualization in python and maybe it is very tough to teach. I don't know , maybe you can do it haha~

    • @dataschool
      @dataschool  6 ปีที่แล้ว

      Thanks for your suggestion! I'll consider it for the future :)

  • @Vatuify
    @Vatuify 5 ปีที่แล้ว

    I think the accuracy is only meaningful for classifications that have three or more classes.

    • @dataschool
      @dataschool  5 ปีที่แล้ว

      No, accuracy is often very meaningful for binary classification problems (2-class).

  • @hadiali5922
    @hadiali5922 4 ปีที่แล้ว

    Hi sir!
    I was wondering and imagining if we could get some videos on how to make use of different machine learning models along with some examples for each model.
    I'm really getting used to your videos as I've already finished pandas and scikit learn playlists.
    So please can you upload some videos on it?
    Or atleast upload some vidoes on unsupervised learning models

    • @dataschool
      @dataschool  4 ปีที่แล้ว

      Thanks for your suggestions!

  • @fisherh9111
    @fisherh9111 3 ปีที่แล้ว

    That background looks like the “Leave Brittany (Spears) Alone!” guy’s background.

  • @arjungoud3450
    @arjungoud3450 3 ปีที่แล้ว

    No more confusing...w