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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.
Tanagra is a free suite of machine learning software for research and academic purposes developed by Ricco Rakotomalala at the Lumière University Lyon 2, France. [1] [2] Tanagra supports several standard data mining tasks such as: Visualization, Descriptive statistics, Instance selection, feature selection, feature construction, regression, factor analysis, clustering, classification and ...
An associative classifier (AC) is a kind of supervised learning model that uses association rules to assign a target value. The term associative classification was coined by Bing Liu et al., [1] in which the authors defined a model made of rules "whose right-hand side are restricted to the classification class attribute".
Download QR code; Print/export ... Classification algorithms (3 C, ... Pages in category "Data mining algorithms" The following 6 pages are in this category, out of 6 ...
Massive Online Analysis (MOA) is a free open-source software project specific for data stream mining with concept drift. It is written in Java and developed at the University of Waikato, New Zealand. [2]
List of GitHub repositories of the project: IBM This data is not pre-processed List of GitHub repositories of the project: IBM Cloud This data is not pre-processed List of GitHub repositories of the project: Build Lab Team This data is not pre-processed List of GitHub repositories of the project: Terraform IBM Modules This data is not pre-processed
In machine learning and statistical classification, multiclass classification or multinomial classification is the problem of classifying instances into one of three or more classes (classifying instances into one of two classes is called binary classification). For example, deciding on whether an image is showing a banana, an orange, or an ...
The COBWEB data structure is a hierarchy (tree) wherein each node represents a given concept. Each concept represents a set (actually, a multiset or bag) of objects, each object being represented as a binary-valued property list. The data associated with each tree node (i.e., concept) are the integer property counts for the objects in that concept.