Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Model Performance Metrics: The Accurac

The video discusses performance measures for models, focusing on accuracy and its limitations. It explains how accuracy is calculated and highlights its drawbacks, especially in cases where different types of errors have different consequences, such as in cancer prediction. The video also introduces mean squared error (MSE) for regression and hints at more advanced measures like confusion matrix, precision, and recall to be covered in the next video.

Why might accuracy not always be the best measure of model performance?

What is mean squared error (MSE) and how is it used in regression analysis?

What additional performance measures are suggested for classification beyond accuracy?