What is a classification model?
A model whose prediction is a class.
classification model explained in plain English
A model whose prediction is a class. For example, the following are all classification models: - A model that predicts an input sentence's language (French? Spanish? Italian?). - A model that predicts tree species (Maple? Oak? Baobab?). - A model that predicts the positive or negative class for a particular medical condition. In contrast, regression models predict numbers rather than classes. Two common types of classification models are: - binary classification - multi-class classification
Example
Practitioners refer to classification model when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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A statistical way of comparing two (or more) techniques—the A and the B.
- ablation
A technique for evaluating the importance of a feature or component by temporarily removing it from a model.
- accuracy
The number of correct classification predictions divided by the total number of predictions.
- activation function
A function that enables neural networks to learn nonlinear (complex) relationships between features and the label.
- active learning
A training approach in which the algorithm chooses some of the data it learns from.
- adaptation
Synonym for tuning or fine-tuning.
- agglomerative clustering
See hierarchical clustering.
- anomaly detection
The process of identifying outliers.
- area under the PR curve
See PR AUC (Area under the PR Curve).
- area under the ROC curve
See AUC (Area under the ROC curve).