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scikit-learn – extends SciPy with a host of machine learning models (classification, clustering, regression, etc.) Shogun (toolbox) – open-source, large-scale machine learning toolbox that provides several SVM (Support Vector Machine) implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R
Early work on statistical classification was undertaken by Fisher, [1] [2] in the context of two-group problems, leading to Fisher's linear discriminant function as the rule for assigning a group to a new observation. [3] This early work assumed that data-values within each of the two groups had a multivariate normal distribution.
In order to build the classification models, the samples belonging to each class need to be analysed using principal component analysis (PCA); only the significant components are retained. For a given class, the resulting model then describes either a line (for one Principal Component or PC), plane (for two PCs) or hyper-plane (for more than ...
Data classification can be viewed as a multitude of labels that are used to define the type of data, especially on confidentiality and integrity issues. [1] Data classification is typically a manual process; however, there are tools that can help gather information about the data. [2] Data sensitivity levels are often proposed to be considered. [2]
Data models represent information areas of interest. While there are many ways to create data models, according to Len Silverston (1997) [7] only two modeling methodologies stand out, top-down and bottom-up: Bottom-up models or View Integration models are often the result of a reengineering effort. They usually start with existing data ...
Data presentation architecture weds the science of numbers, data and statistics in discovering valuable information from data and making it usable, relevant and actionable with the arts of data visualization, communications, organizational psychology and change management in order to provide business intelligence solutions with the data scope ...
000 Computer science, information and general works; 001 Knowledge; 002 The book (writing, libraries, and book-related topics) 003 Systems; 004 Data processing and computer science; 005 Computer programming, programs, and data; 006 Special computer methods (e.g. AI, multimedia, VR) [4] 007–009 [Unassigned] 010 Bibliographies. 010 Bibliography ...
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".