Intro to Machine Learning | Part 5.1: F1, Accuracy, and ROC example

Hello and welcome to today's video. Today, we are discussing an example student grades dataset and calculating the following metrics using that dataset: F1 score, Accuracy, Micro/Macro averaging, Precision, Recall, ROC, and AUROC This will be another step towards learning the basics of Machine Learning. I hope you can sit back, relax, and enjoy. Please feel free to discuss anything mentioned in the video down in the comments. I am just starting out, so if you have any advice/suggestions for me, please leave them in the comments. Thank you for watching, and taking the time to read. ---------------------------------------------------------------------- LINKS: StackOverflow answer explaining F1 score, Precision, Recall, and ROC: https://stackoverflow.com/a/52892413 (By user: Yahya) ---------------------------------------------------------------------- Timestamps: 00:00 Intro 00:54 Explaining the dataset 05:25 TP, FP, TN, FN values 10:08 Accuracy 11:03 Precision 11:36 Recall 12:10 F1 score 13:39 ROC 25:50 Creating ROC plot 29:52 AUROC curve 33:11 Overview 34:26 Outro

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