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  2. SEMMA - Wikipedia

    en.wikipedia.org/wiki/SEMMA

    SEMMA mainly focuses on the modeling tasks of data mining projects, leaving the business aspects out (unlike, e.g., CRISP-DM and its Business Understanding phase). Additionally, SEMMA is designed to help the users of the SAS Enterprise Miner software. Therefore, applying it outside Enterprise Miner may be ambiguous. [3]

  3. Group method of data handling - Wikipedia

    en.wikipedia.org/wiki/Group_method_of_data_handling

    Group method of data handling (GMDH) is a family of inductive algorithms for computer-based mathematical modeling of multi-parametric datasets that features fully automatic structural and parametric optimization of models.

  4. JMP (statistical software) - Wikipedia

    en.wikipedia.org/wiki/JMP_(statistical_software)

    JMP Pro is intended for data scientists, and has an emphasis on advanced predictive modelling and model selection. [41] JMP Genomics, used for analyzing and visualizing genomics data, [49] requires a SAS component to operate and can access SAS/Genetics and SAS/STAT procedures or invoke SAS macros. [48]

  5. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Group model s: some algorithms do not provide a refined model for their results and just provide the grouping information. Graph-based model s : a clique , that is, a subset of nodes in a graph such that every two nodes in the subset are connected by an edge can be considered as a prototypical form of cluster.

  6. SAS (software) - Wikipedia

    en.wikipedia.org/wiki/SAS_(software)

    SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it. [3] SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

  8. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g., using data modeling:

  9. pSeven - Wikipedia

    en.wikipedia.org/wiki/PSeven

    pSeven is a design space exploration (DSE) software platform that was developed by pSeven SAS that features design, simulation, and analysis capabilities and assists in design decisions. It provides integration with third-party CAD and CAE software tools; multi-objective and robust optimization algorithms; data analysis , and uncertainty ...