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  2. Anomaly detection - Wikipedia

    en.wikipedia.org/wiki/Anomaly_detection

    ELKI is an open-source Java data mining toolkit that contains several anomaly detection algorithms, as well as index acceleration for them. PyOD is an open-source Python library developed specifically for anomaly detection. [52] scikit-learn is an open-source Python library that contains some algorithms for unsupervised anomaly detection.

  3. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]

  4. Unsupervised learning - Wikipedia

    en.wikipedia.org/wiki/Unsupervised_learning

    Some of the most common algorithms used in unsupervised learning include: (1) Clustering, (2) Anomaly detection, (3) Approaches for learning latent variable models. Each approach uses several methods as follows: Clustering methods include: hierarchical clustering, [13] k-means, [14] mixture models, model-based clustering, DBSCAN, and OPTICS ...

  5. Isolation forest - Wikipedia

    en.wikipedia.org/wiki/Isolation_forest

    Isolation Forest is an algorithm for data anomaly detection using binary trees.It was developed by Fei Tony Liu in 2008. [1] It has a linear time complexity and a low memory use, which works well for high-volume data.

  6. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    When viewed as a graph, a network of computers can be analyzed with GNNs for anomaly detection. Anomalies within provenance graphs often correlate to malicious activity within the network. GNNs have been used to identify these anomalies on individual nodes [ 47 ] and within paths [ 48 ] to detect malicious processes, or on the edge level [ 49 ...

  7. One-class classification - Wikipedia

    en.wikipedia.org/wiki/One-class_classification

    The term one-class classification (OCC) was coined by Moya & Hush (1996) [8] and many applications can be found in scientific literature, for example outlier detection, anomaly detection, novelty detection. A feature of OCC is that it uses only sample points from the assigned class, so that a representative sampling is not strictly required for ...

  8. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    Keyword Detection: Autoencoders can be trained to identify keywords and important concepts within the content of web pages. This can assist in optimizing keyword usage for better indexing. Semantic Search: By using autoencoder techniques, semantic representation models of content can be created. These models can be used to enhance search ...

  9. Category:Computer graphics algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Computer_graphics...

    Edge detection (9 P) G. ... Pages in category "Computer graphics algorithms" The following 49 pages are in this category, out of 49 total. ... Phong reflection model;

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