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  2. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    In machine learning, we can handle various types of data, e.g. audio signals and pixel values for image data, and this data can include multiple dimensions. Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance.

  3. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  4. Non-negative matrix factorization - Wikipedia

    en.wikipedia.org/wiki/Non-negative_matrix...

    For example, if V is an m × n matrix, W is an m × p matrix, and H is a p × n matrix then p can be significantly less than both m and n. Here is an example based on a text-mining application: Let the input matrix (the matrix to be factored) be V with 10000 rows and 500 columns where words are in rows and documents are in columns.

  5. One-class classification - Wikipedia

    en.wikipedia.org/wiki/One-class_classification

    In machine learning, one-class classification (OCC), also known as unary classification or class-modelling, tries to identify objects of a specific class amongst all objects, by primarily learning from a training set containing only the objects of that class, [1] although there exist variants of one-class classifiers where counter-examples are used to further refine the classification boundary.

  6. Andrew Furco - Wikipedia

    en.wikipedia.org/wiki/Andrew_Furco

    Andrew Furco (born April 17, 1961) is an American scholar, researcher, and educator in the field of experiential education, whose work has focused primarily on advancing research in service learning. Service learning is an instructional approach whereby students participate in community service that is linked to their academic learning. [1]

  7. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...

  8. Service learning programs - Wikipedia

    en.wikipedia.org/wiki/Service_learning_programs

    At Purdue University, service-learning focused on the education and academic aspect of service-learning: a) participate in an organized service activity that meets community-identified needs; b) use knowledge and skills directly related to a course, discipline and/or specific learning outcomes; and c) reflect on the service activity in such a ...

  9. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. [1] Choosing informative, discriminating, and independent features is crucial to produce effective algorithms for pattern recognition, classification, and regression tasks.