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  2. 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 .

  3. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future. [3] 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 ...

  4. Stock market prediction - Wikipedia

    en.wikipedia.org/wiki/Stock_market_prediction

    The successful prediction of a stock's future price could yield significant profit. The efficient market hypothesis suggests that stock prices reflect all currently available information and any price changes that are not based on newly revealed information thus are inherently unpredictable. Others disagree and those with this viewpoint possess ...

  5. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    A machine learning model is a type of mathematical model that, once "trained" on a given dataset, can be used to make predictions or classifications on new data. During training, a learning algorithm iteratively adjusts the model's internal parameters to minimize errors in its predictions. [ 84 ]

  6. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    The first clinical prediction model reporting guidelines were published in 2015 (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD)), and have since been updated. [10] Predictive modelling has been used to estimate surgery duration.

  7. Automated machine learning - Wikipedia

    en.wikipedia.org/wiki/Automated_machine_learning

    Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of automation and ML. [1] AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.

  8. Structured prediction - Wikipedia

    en.wikipedia.org/wiki/Structured_prediction

    Structured prediction or structured output learning is an umbrella term for supervised machine learning techniques that involves predicting structured objects, rather than discrete or real values. [ 1 ]

  9. Ensemble learning - Wikipedia

    en.wikipedia.org/wiki/Ensemble_learning

    It involves training another learning model to decide which of the models in the bucket is best-suited to solve the problem. Often, a perceptron is used for the gating model. It can be used to pick the "best" model, or it can be used to give a linear weight to the predictions from each model in the bucket.