Glossary · Phase 3 · Machine learning
Feature
One input column a model learns from, such as a customer's age or number of orders.
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The target decides which models and which scores you can use.
Learn it properly
Features and labels · Supervised learning: inputs, targets and predictions. About 25 minutes.
Other terms from the same lesson
- binary classification: Classification with exactly two possible answers, such as churn yes or no.
- classification: Predicting which category something belongs to, such as spam or not spam.
- label: The right answer for an example, which the model learns to predict.
- regression: Predicting a number, such as next month's sales.
- supervised learning: Learning from examples that come with the right answers.
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