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  2. Cost-sensitive machine learning - Wikipedia

    en.wikipedia.org/.../Cost-sensitive_machine_learning

    The cost matrix is a crucial element within cost-sensitive modeling, [2] explicitly defining the costs or benefits associated with different prediction errors in classification tasks. Represented as a table, the matrix aligns true and predicted classes, assigning a cost value to each combination.

  3. 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 .

  4. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    In 2018, Banerjee et al. [17] proposed a deep learning model for estimating short-term life expectancy (>3 months) of the patients by analyzing free-text clinical notes in the electronic medical record, while maintaining the temporal visit sequence. The model was trained on a large dataset (10,293 patients) and validated on a separated dataset ...

  5. 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.

  6. Stochastic modelling (insurance) - Wikipedia

    en.wikipedia.org/wiki/Stochastic_modelling...

    Claims inflations can be applied, based on the inflation simulations that are consistent with the outputs of the asset model, as are dependencies between the losses of different portfolios. The relative uniqueness of the policy portfolios written by a company in the general insurance sector means that claims models are typically tailor-made.

  7. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

  8. Prediction: Here's How Much Auto Insurance Will Go Up in 2025

    www.aol.com/prediction-heres-much-auto-insurance...

    The cost of an average auto insurance policy will rise by 22% in 2024, and residents of some states could see the cost of coverage rise by 50% or more, according to Insurify. And this is on top of ...

  9. Uplift modelling - Wikipedia

    en.wikipedia.org/wiki/Uplift_modelling

    Yong (2015) combined a mathematical optimization algorithm via dynamic programming with machine learning methods to optimally stratify patients. [ 14 ] Uplift modelling is a special case of the older psychology concept of Differential Prediction. [ 15 ]