April 2019
Intermediate to advanced
426 pages
11h 13m
English
Content preview from Mastering Python for Finance - Second Edition
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Loss functions
The loss function computes the error between the predicted value of a model and the actual value. The smaller the error value, the better the model is in prediction. Some loss functions used in regression-based models are:
- Mean squared error (MSE) loss
- Mean absolute error (MAE) loss
- Huber loss
- Quantile loss
Some loss functions used in classification-based models are:
- Focal loss
- Hinge loss
- Logistic loss
- Exponential loss
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