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  2. Batch normalization - Wikipedia

    en.wikipedia.org/wiki/Batch_normalization

    In a neural network, batch normalization is achieved through a normalization step that fixes the means and variances of each layer's inputs. Ideally, the normalization would be conducted over the entire training set, but to use this step jointly with stochastic optimization methods, it is impractical to use the global information.

  3. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    A particular problem with BatchNorm is that during training, the mean and variance are calculated on the fly for each batch (usually as an exponential moving average), but during inference, the mean and variance were frozen from those calculated during training. This train-test disparity degrades performance.

  4. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines, logistic regression, and artificial neural networks).

  5. Health care analytics - Wikipedia

    en.wikipedia.org/wiki/Health_care_analytics

    Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...

  6. Normalization (statistics) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(statistics)

    In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the intention is to bring the entire probability distributions of adjusted values into alignment.

  7. Glossary of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_artificial...

    batch normalization A technique for improving the performance and stability of artificial neural networks. It is a technique to provide any layer in a neural network with inputs that are zero mean/unit variance. [48] Batch normalization was introduced in a 2015 paper.

  8. Health administration - Wikipedia

    en.wikipedia.org/wiki/Health_administration

    Iconographic Collections. Keywords: E. Walker; Florence Nightingale; W.J. Simpson. Health administration, healthcare administration, healthcare management or hospital management is the field relating to leadership, management, and administration of public health systems, health care systems, hospitals, and hospital networks in all the primary, secondary, and tertiary sectors.

  9. Normalization process model - Wikipedia

    en.wikipedia.org/wiki/Normalization_process_model

    The normalization process model is a sociological model, developed by Carl R. May, that describes the adoption of new technologies in health care.The model provides framework for process evaluation using three components – actors, objects, and contexts – that are compared across four constructs: Interactional workability, relational integration, skill-set workability, and contextual ...