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  2. Residual sum of squares - Wikipedia

    en.wikipedia.org/wiki/Residual_sum_of_squares

    A small RSS indicates a tight fit of the model to the data. It is used as an optimality criterion in parameter selection and model selection. In general, total sum of squares = explained sum of squares + residual sum of squares. For a proof of this in the multivariate ordinary least squares (OLS) case, see partitioning in the general OLS model.

  3. Lack-of-fit sum of squares - Wikipedia

    en.wikipedia.org/wiki/Lack-of-fit_sum_of_squares

    In statistics, a sum of squares due to lack of fit, or more tersely a lack-of-fit sum of squares, is one of the components of a partition of the sum of squares of residuals in an analysis of variance, used in the numerator in an F-test of the null hypothesis that says that a proposed model fits well.

  4. Neural network (machine learning) - Wikipedia

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

    An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. Artificial neuron models that mimic biological neurons more closely have also been recently investigated and shown to significantly improve performance. These are connected by edges, which model the synapses in the brain. Each ...

  5. PRESS statistic - Wikipedia

    en.wikipedia.org/wiki/PRESS_statistic

    Models that are over-parameterised (over-fitted) would tend to give small residuals for observations included in the model-fitting but large residuals for observations that are excluded. The PRESS statistic has been extensively used in lazy learning and locally linear learning to speed-up the assessment and the selection of the neighbourhood size.

  6. Artificial neuron - Wikipedia

    en.wikipedia.org/wiki/Artificial_neuron

    Artificial neurons are designed to mimic aspects of their biological counterparts. However a significant performance gap exists between biological and artificial neural networks. In particular single biological neurons in the human brain with oscillating activation function capable of learning the XOR function have been discovered. [6]

  7. Computational cognition - Wikipedia

    en.wikipedia.org/wiki/Computational_cognition

    When computational models attempt to mimic human cognitive functioning, all the details of the function must be known for them to transfer and display properly through the models, allowing researchers to thoroughly understand and test an existing theory because no variables are vague and all variables are modifiable.

  8. Mathematics of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Mathematics_of_artificial...

    Sometimes models are intimately associated with a particular learning rule. A common use of the phrase "ANN model" is really the definition of a class of such functions (where members of the class are obtained by varying parameters, connection weights, or specifics of the architecture such as the number of neurons, number of layers or their ...

  9. Brain simulation - Wikipedia

    en.wikipedia.org/wiki/Brain_simulation

    The Blue Brain Project Showcase likewise illustrates how models and data from the Blue Brain Project can be converted to NeuroML and PyNN (Python neuronal network models). [5] The Brain Simulation Platform (BSP) is an internet-accessible open collaboration platform for brain simulation, created by the Human Brain Project. [35]