Precision and Recall - Machine Learning Classification Metrics - DataMites ML Courses

Precision and Recall - Machine Learning Classification Metrics
Trainer: Trainer Mr. Ashok Veda, You can follow him @ / ashokveda
In this video, Mr. Ashok explained Precision and Recall in-detail.
Before watching this Watch our previous videos,
ROC Curve and AUC Score - Machine Learning Classification Metrics Python: • ROC Curve and AUC Scor...
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All the best.

[@sattarshaik8161]

excellent explanation sir, I got totally confused precision and recall. But as per ur session, it's clear.

[@DataMites]

Glad to hear that

[@ducle7970]

Hi sir, I'm going to finish my bachelor's degree in Maths and CS, this series very helpful to me for my interview preparation. I appreciate your well explaination. Thanks a lot!

[@DataMites]

All the best

[@kasifnasim7344]

Very intellectual video sir

[@DataMites]

Thank You!

[@louatisofiene9114]

Very well explained

[@DataMites]

Thanks You!

[@kw9200]

HI sir, can I ask if I am currently doing a project on predicting earthquake damages Grade 1/2/3. The recall must be high am I right? Also, because its an imbalanced data set, is it right that I use SMOTE to balanced it? thank you so much

[@DataMites]

Hi, Please use SMOTE. for more information visit: imbalanced-learn.org/stable/generated/imblearn.over_sampling.SMOTE.html

[@chandanaenugala2527]

Very well explained sir, in the classification report we can see the precision and recall for class 0 how are those caluculated manually pls help me out

[@DataMites]

Hi, Please refer this page to know the formulas of precision and recall en.wikipedia.org/wiki/Precision_and_recall