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
Supervised Learning
Machine learning approach where models learn from labeled training data to predict outcomes.
Unsupervised Learning
Machine learning approach where models find patterns in data without labeled examples.
Semi-Supervised Learning
Machine learning approach using a small amount of labeled data with a large amount of unlabeled data.
Classification
Predicting which category or class an input belongs to from a set of predefined categories.
Regression
Predicting a continuous numerical value based on input features.
Feature
An individual measurable property or characteristic of data used as input to a machine learning model.
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