Underfitting
When a model is too simple to capture the underlying patterns in the data.
In-depth explanation
Underfitting occurs when a model lacks the complexity to learn the relationship between inputs and outputs. Signs include poor performance on both training and validation data. Solutions include using more complex models, adding features, reducing regularization, or training longer.
Examples
Related terms
More in Machine Learning
Classification
Predicting which category or class an input belongs to from a set of predefined categories.
Cross-Validation
A technique to evaluate model performance by training and testing on different subsets of data.
Ensemble Learning
Combining multiple models to produce better predictions than any single model.
Feature
An individual measurable property or characteristic of data used as input to a machine learning model.
Feature Engineering
The process of using domain knowledge to create new features that improve model performance.
Gradient Descent
An optimization algorithm that iteratively adjusts model parameters to minimize the loss function.
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