Feature
An individual measurable property or characteristic of data used as input to a machine learning model.
In-depth explanation
Features are the variables that the model uses to make predictions. Good features capture relevant information and discriminate between different outputs. Feature engineering—creating new features from raw data—is often crucial for model performance. Features can be numerical, categorical, text, images, or other data types.
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 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.
Hyperparameter
Configuration settings set before training that control the learning process, not learned from data.
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