Answer Posted / Divya Prakash Gupta

Model Performance encompasses a range of metrics including accuracy, precision, recall, F1 score, ROC-AUC, etc., which provide a comprehensive evaluation of the model's ability to generalize well. While Accuracy is one aspect of model performance, it may not always be the most appropriate or useful metric due to class imbalance, skewed data distributions, or other factors. Therefore, it's crucial to consider multiple performance metrics when evaluating a machine learning model.

Tell us do you have research experience in machine learning?

150

Tell me what are the last machine learning papers you've read?

209

Do you have research experience in machine learning?

74

What are standardization and normalisation? Give one advantage of each over the other?

74