Machine Learning
23 views
Overfitting
Quick Definition
When a model learns training data noise and fails on new data
Full Definition
A modeling error where a model learns noise in training data, negatively impacting performance on new data.
Examples
high variance, poor generalization, complex models
Related Terms
regularization
cross-validation
underfitting
More Machine Learning Terms
Gradient Descent
Optimization algorithm minimizing loss by steepest descent
Confusion Matrix
Table visualizing classifier performance by class predictions
Batch Normalization
Normalizing layer inputs to stabilize and speed up training
Feature Engineering
Creating and transforming input variables to improve performance
Boosting
Sequentially combining weak learners correcting previous errors
Kernel Trick
Transforming data to higher dimensions for linear separability