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In this video. we'll explore accuracy and the confusion matrix, unraveling the concepts of Type 1 and Type 2 errors. Join us on this journey to understand how these metrics play a crucial role in evaluating the performance of classification models. Code used: https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day59-classification-metrics ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected] ⌚Time Stamps⌚ 00:00 - Intro 00:46 - Accuracy 06:25 - Code Example using SKL 08:35 - Accuracy of multi-classification problem 10:18 - How much accuracy is good? 13:16 - The problem with Accuracy Score 15:30 - Confusion Matrix 23:15 - Type 1 Error 25:53 - Confusion Matrix for Multi Classification Problem 30:03 - When is accuracy misleading?
