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  2. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics can help underwrite these quantities by predicting the chances of illness, default, bankruptcy, etc. Predictive analytics can streamline the process of customer acquisition by predicting the future risk behavior of a customer using application level data. Predictive analytics in the form of credit scores have reduced the ...

  3. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  4. Cloud analytics - Wikipedia

    en.wikipedia.org/wiki/Cloud_Analytics

    Cloud analytics is designed to make official statistical data readily categorized and available via the users web browser. The global Cloud Analytics Market size is expected to grow from USD 35.7 billion in 2024 to USD 118.5 billion in 2029, at a CAGR of 27.1% during the forecast period, according to a new report by MarketsandMarkets™. [3]

  5. Prescriptive analytics - Wikipedia

    en.wikipedia.org/wiki/Prescriptive_analytics

    Prescriptive analytics is the third and final phase of business analytics, which also includes descriptive and predictive analytics. [2] [3] Referred to as the "final frontier of analytic capabilities", [4] prescriptive analytics entails the application of mathematical and computational sciences and suggests decision options for how to take advantage of the results of descriptive and ...

  6. Data Science and Predictive Analytics - Wikipedia

    en.wikipedia.org/wiki/Data_Science_and...

    The significantly reorganized revised edition of the book (2023) [2] expands and modernizes the presented mathematical principles, computational methods, data science techniques, model-based machine learning and model-free artificial intelligence algorithms. The 14 chapters of the new edition start with an introduction and progressively build ...

  7. SAP HANA - Wikipedia

    en.wikipedia.org/wiki/SAP_HANA

    During the early development of SAP HANA, a number of technologies were developed or acquired by SAP SE.These included TREX search engine (in-memory column-oriented search engine), P*TIME (in-memory online transaction processing (OLTP) Platform acquired by SAP in 2005), and MaxDB with its in-memory liveCache engine.

  8. Predictive learning - Wikipedia

    en.wikipedia.org/wiki/Predictive_learning

    Predictive learning is a machine learning (ML) technique where an artificial intelligence model is fed new data to develop an understanding of its environment, capabilities, and limitations. This technique finds application in many areas, including neuroscience , business , robotics , and computer vision .

  9. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    Predictive modelling uses statistics to predict outcomes. [1] Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. [2]