Classification

How it is used

Binary classification has two classes, such as yes and no; multi-class classification has more. You train a classifier and measure it with accuracy, precision, recall and a confusion matrix.

Example sentences

1. Fraud detection is a binary classification problem with very few positive cases.

2. We're testing three classification models to route support tickets automatically.

Common collocations

• binary classification
• classification model
• multi-class classification
• classification problem

Related terms

• regressionA family of methods that model how a numeric outcome, such as sales or price, depends on one or more input variables, used to estimate effects or make predictions.
• accuracyThe share of all predictions that a model gets right; for example, 90 correct predictions out of 100 means an accuracy of 90%.
• precisionOf all the cases a model labels as positive, the share that really are positive; high precision means few false alarms.
• recallOf all the cases that really are positive, the share that a model correctly finds; high recall means the model misses few real cases.
• modelA mathematical representation of a real process, built from data, that is used to explain relationships or to make predictions about new cases.

This word in other fields

The same English word can have a different meaning in another field:

• classification · Software Engineering
• classification · Artificial Intelligence & Machine Learning

More terms: Modelling and Machine Learning

• feature
• training data
• overfitting
• cross-validation
• baseline
• feature engineering
• target variable
• test set
• clustering