Identifying which category an object belongs to.
Applications: Spam detection, image recognition.
Predicting a continuous-valued attribute associated with an object.
Applications: Drug response, Stock prices.
Automatic grouping of similar objects into sets.
Applications: Customer segmentation, Grouping experiment outcomes
Reducing the number of random variables to consider.
Applications: Visualization, Increased efficiency
non-negative matrix factorization,
Comparing, validating and choosing parameters and models.
Applications: Improved accuracy via parameter tuning
Feature extraction and normalization.
Applications: Transforming input data such as text for use with machine learning algorithms.
scikit-learn development and maintenance are financially supported by