Confusion Matrix Solved Example Accuracy Precision Recall F1 Score Prevalence by Mahesh Huddar

Confusion Matrix Solved Example Accuracy, Precision, Recall, F1 Score, Sensitivity, Specificity Prevalence in Machine Learning by Mahesh Huddar
The following concepts are discussed:
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confusion matrix in ML,
confusion matrix terminology,
performance of a classification model,
Performance metric,
performance metric machine learning,
example confusion matrix for the binary classifier,
Accuracy machine learning model,
Misclassification Rate in ML,
True Positive Rate of classifier
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[@MaheshHuddar]

F1 score = (2*precision*recall)/(precision+recall)

[@cromllo7162]

how did you get the answers in percentages?

[@notfixedcontent_12]

Multiply with 100

[@mjay5655]

i got 95 as the answer for F1

[@RoyBombale]

@@cromllo7162 multiply them into 100

[@tuheen7668]

Now I know why it is called CONFUSION matrix......but you explained very well sir!

[@MaheshHuddar]

Thank You
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[@insha9862]

Thank you very much sir

[@Rihanvlog0786]

Hii

[@MaheshHuddar]

Most welcome
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[@digitalmediatechconsultant]

Thanks for your explanation. You sucessfully, removed the Confusion from the Confusion Matrix

[@MaheshHuddar]

You're welcome
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[@menagasaravanan1027]

Thanks u sir ur explanation is superb

[@MaheshHuddar]

Welcome
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[@ayotolu-f4f]

Best Statistical explanation I have ever encountered thanks 😊

[@MaheshHuddar]

Welcome
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[@Xmenbasketbol]

Thanks for the simple explanation

[@MaheshHuddar]

Welcome
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[@adisimhaa65]

SHORT AND CLEAR
thank you

[@MaheshHuddar]

Welcome
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[@sakshikadel16]

thank you sir understood very well....

[@MaheshHuddar]

You are most welcome
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[@sakshikadel16]

@@MaheshHuddar sure sir

[@ShivamSingh-te9tl]

Thank you so much sir, and also Happy Teacher's day :)

[@MaheshHuddar]

Welcome
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[@spoorthib2496]

If more than one model is present based on what we need to select one particular model ie based on high accuracy or precision or recall?

[@chrisogonas]

Superb!

[@MaheshHuddar]

Thank You
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[@chrisogonas]

@@MaheshHuddar Absolutely!

[@thestudyexplanation7052]

THNAKSS UUUU SOO MUCHHHH SIRRRRR :))))

[@MaheshHuddar]

Welcome
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[@a_13_ashishgaikwad]

Thanks Sir

[@MaheshHuddar]

Welcome
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[@Rider-jn6zh]

Can u please let us know when and which accuracy metric we can consider for our problem among accuracy, precision,recall and f1-score

[@3srkingdom]

Thanku sir❤

[@MaheshHuddar]

Welcome
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[@Rupesh-u8t]

nicer sir thanks

[@MaheshHuddar]

Welcome
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[@AJAmr99]

thank you, bro

[@MaheshHuddar]

Welcome
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[@abizarkhalil]

plz calculate WEIGHTED ACCURACY from the confusion matrix (two class)

[@mohamedjamaludeen7179]

Nice

[@MaheshHuddar]

Welcome
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[@VineethMenonk]

Super bhai

[@MaheshHuddar]

Thank You
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[@santoshkumarsahu8482]

When we prefer accuracy, precision, recall and f1 score??

[@Doesitmatter8191]

but the accuracy when calculated is , 45.63333 .... how does it come 93.33 % to uh sir ?

[@MaheshHuddar]

You are wrong
Watch video one more time carefully

[@areejawan]

@@MaheshHuddar ans is 140/150 equals to 0.9333

[@notfixedcontent_12]

To get the value in presentage we need multiple with 100

[@jeevithasrinivasan3199]

45+95 = 140 ... 140/150 = 0.9333
0.933 * 100 = 93.33%

[@jishnupm7144]

thanks

[@MaheshHuddar]

Welcome
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[@ahsanmemon8943]

What can we do for a big matrix 10*10

[@alphapranay214]

Pooja 🫖

[@humbleakh]

​@@alphapranay214😂😂

[@black8august410]

​@@alphapranay214 😆

[@RD-td6hg]

Thank you. This shit confuses the hell out of me. You explained it very well

[@MaheshHuddar]

Welcome
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[@PSTWFB]

#confusion#matrix#machinelearning#deep#precision#recall F1 #score#accuracy#true#positive #negative!
ruclips.net/video/YlFgsaxagX0/видео.html

[@Zaid-bf1qp]

How about support?

[@kentimancy]

legend

[@MaheshHuddar]

Welcome
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[@rithikareddy3821]

What is no information rate?

[@maanwit4318]

Send me the example please

[@asifnazir8965]

f1 score?

[@MaheshHuddar]

F1 score = (2*precision*recall)/(precision+recall)

[@asifnazir8965]

Thank you so much sir..u r the best teacher...live long🥰🥰🥰

[@MaheshHuddar]

@@asifnazir8965 Thank You
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[@amitgupta624]

Thank you sir

[@MaheshHuddar]

Welcome
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[@notfixedcontent_12]

Thank You sir
Very much

[@MaheshHuddar]

Welcome
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[@Elena_9152]

Thank you sir

[@MaheshHuddar]

Welcome
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