Day #88 - Metrics Optimization

Loss vs Metric

• Metric - Function which we want to use to evaluate the model. Maximum accuracy in classification
• Optimization Loss - Easy to optimize for given model, Function our model optimizes. MSE, LogLoss
• Preprocess train and optimize another metric - MSPE, MAPE, RMSLE
• Optimize another metric postprocess predictions - Accuracy, Kapps
• Early Stopping - Stop traning when models starts to overfit

 Custom loss functions

Accuracy Metrics

Happy Coding and Learning!!!