How to evaluate a classifier in scikit-learn

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In this video, you'll learn how to properly evaluate a classification model using a variety of common tools and metrics, as well as how to adjust the performance of a classifier to best match your business objectives. I'll start by demonstrating the weaknesses of classification accuracy as an evaluation metric. I'll then discuss the confusion matrix, the ROC curve and AUC, and metrics such as sensitivity, specificity, and precision. By the end of the video, you will have a solid foundation for intelligently evaluating your own classification model.

== CONFUSION MATRIX RESOURCES ==

== ROC/AUC RESOURCES ==

== OTHER RESOURCES ==

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This 1-hour video was clearer and more comprehensive that half of a semester in my uni! Thank you so much!

konradd
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I love how you frame a question and then go about answering it, step by step, along with the viewer.
So many instructors simply venture forth with explaining something, assuming along the way that the student knows exactly where they are heading. Also, it helps to compartmentalize the learning for the student; minimizing confusion.

charlescoult
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It has been more than 2 years since you made this video but is still one of the best out there and incredibly helpful. The delivery style is something that makes it easier to follow.

Thank you for a great tutorial Kevin..!

sandeepkrishnan
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I have to say that I am very grateful for the way you are giving these lessons. You are the master, thank you!

kmillanr
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This is hands down One of the best series I've ever watched. Your execution is flawless

tahaanwar
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Most relevant topics taught in very simple words and code snippets. Explanations are to the point and examples are perfect. Thanks for these videos.

menont
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This video is just perfect and cleared most of the confusion that I have always had concerning this topic

nriezedichisom
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Did I tell you that you are simply awesome?!
Your concepts and their delivery is simply DIVINE!!

Thank you very much sir, but yeah you made me fall in love with python and data science!
" Become a data scientist " - My new year resolution for 2016 !!

adamyatripathi
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Finally made time to finish watching and going along with the video.
Yeah, a lot of good material - 'especially' for a someone kinda new to this game. A LOT of material to munch on and try to remember (even with practice).
Thanks for posting.

gudguya
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your teaching level is god level got crystal clear in just one go!

parthbhardwaj
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Thank you so much. I found this video because I have an imbalanced dataset for a binary classification. Now i understand the whole picture !

xKratareJrx
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You're a legend buddy! I've sifted videos after videos for good explanation of confusion matrix. None came close to yours. Lots of people might have a PhD in the topic, but not all are good tutors.

shanxW
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This course is a master class:
Well delivered content, at a digestible paste.

Thank you very much.

Regards

Elvy

elvykamunyokomanunebo
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This is like the best corner of Youtube for practical machine learning code + explaination. Thank you so much!

glowish
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Bruh... You are the man, YOU ARE THE MAN!!! False Positive = FALSELY PREDICTED POSITIVE.
That's just fucking genius. I've been trying to understand these for the past 2 days man. And you did it in 10 secs. Damn good job ma man

syedhasan
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I searched quite a lot and only here found out how to change the classifier threshold, thanks!

Gaarv
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Thank you so much!! Extremely clearly explained. For me, it has been among the most useful tutorials that I ever went through on YouTube.

Jan-wgkn
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Hi there. I just found your channel yesterday and subscribed immediately. Thanks for the information you provided here with a great accent and diction.

orkuntahiraran
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Hi Kevin, Today only I have started looking into your videos on Machine Learning. So far, I have gone through three videos and it's awesome. Your teaching style is so very nice that it's really outstanding for beginners even. Carry ON...it's wonderful.

debasishhazra
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Wonderful teaching, granularity of explanation is exceptional. Thank you.

chidanandamurthyp
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