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  2. Microsoft Analysis Services - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Analysis_Services

    Microsoft SQL Server Analysis Services (SSAS [1]) is an online analytical processing (OLAP) and data mining tool in Microsoft SQL Server.SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables or files.

  3. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while remaining concise enough to be mined within an acceptable time limit. A common source for data is a data mart or data ...

  4. List of text mining methods - Wikipedia

    en.wikipedia.org/wiki/List_of_text_mining_methods

    Different text mining methods are used based on their suitability for a data set. Text mining is the process of extracting data from unstructured text and finding patterns or relations. Below is a list of text mining methodologies. Centroid-based Clustering: Unsupervised learning method. Clusters are determined based on data points. [1]

  5. Vowpal Wabbit - Wikipedia

    en.wikipedia.org/wiki/Vowpal_Wabbit

    Vowpal wabbit has been used to learn a tera-feature (10 12) data-set on 1000 nodes in one hour. [1] Its scalability is aided by several factors: Out-of-core online learning: no need to load all data into memory; The hashing trick: feature identities are converted to a weight index via a hash (uses 32-bit MurmurHash3)

  6. 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.

  7. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    This kind of data redundancy due to the spatial correlation between sensor observations inspires the techniques for in-network data aggregation and mining. By measuring the spatial correlation between data sampled by different sensors, a wide class of specialized algorithms can be developed to develop more efficient spatial data mining algorithms.

  8. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text.It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources."

  9. ELKI - Wikipedia

    en.wikipedia.org/wiki/ELKI

    Version 0.4 (September 2011) added algorithms for geo data mining and support for multi-relational database and index structures. [ 10 ] Version 0.5 (April 2012) focuses on the evaluation of cluster analysis results, adding new visualizations and some new algorithms.