Machine Learning
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Loss Function
Quick Definition
Math function measuring prediction vs actual value difference
Full Definition
A mathematical function measuring the difference between model predictions and actual target values.
Examples
cross-entropy, MSE, MAE, hinge loss, focal loss
Related Terms
gradient-descent
optimization
More Machine Learning Terms
Underfitting
When a model is too simple to capture data patterns
Hidden Markov Model
Statistical model with hidden states and observable outputs
Data Augmentation
Artificially increasing training data through modified copies
CatBoost
Gradient boosting library with native categorical feature support
A/B Testing
Statistical method comparing two versions for performance
Feature Engineering
Creating and transforming input variables to improve performance