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  2. Squared deviations from the mean - Wikipedia

    en.wikipedia.org/wiki/Squared_deviations_from...

    Squared deviations from the mean (SDM) result from squaring deviations. In probability theory and statistics, the definition of variance is either the expected value of the SDM (when considering a theoretical distribution) or its average value (for actual experimental data). Computations for analysis of variance involve the partitioning of a ...

  3. Partial least squares path modeling - Wikipedia

    en.wikipedia.org/wiki/Partial_least_squares_path...

    The partial least squares path modeling or partial least squares structural equation modeling (PLS-PM, PLS-SEM) [1] [2] [3] is a method for structural equation modeling that allows estimation of complex cause-effect relationships in path models with latent variables.

  4. Cap Gemini SDM - Wikipedia

    en.wikipedia.org/wiki/Cap_Gemini_SDM

    Cap Gemini SDM, or SDM2 (System Development Methodology) is a software development method developed by the software company Pandata in the Netherlands in 1970. The method is a waterfall model divided in seven phases that have a clear start and end.

  5. STELLA (programming language) - Wikipedia

    en.wikipedia.org/wiki/STELLA_(programming_language)

    STELLA (short for Systems Thinking, Experimental Learning Laboratory with Animation; also marketed as iThink) is a visual programming language for system dynamics modeling introduced by Barry Richmond in 1985.

  6. Random effects model - Wikipedia

    en.wikipedia.org/wiki/Random_effects_model

    In econometrics, a random effects model, also called a variance components model, is a statistical model where the model parameters are random variables.It is a kind of hierarchical linear model, which assumes that the data being analysed are drawn from a hierarchy of different populations whose differences relate to that hierarchy.

  7. Hinge loss - Wikipedia

    en.wikipedia.org/wiki/Hinge_loss

    The plot shows that the Hinge loss penalizes predictions y < 1, corresponding to the notion of a margin in a support vector machine. In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification, most notably for support vector machines (SVMs). [1]

  8. Deep belief network - Wikipedia

    en.wikipedia.org/wiki/Deep_belief_network

    In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple layers of latent variables ("hidden units"), with connections between the layers but not between units within each layer.

  9. Pulse-width modulation - Wikipedia

    en.wikipedia.org/wiki/Pulse-width_modulation

    Pulse-width modulation (PWM), also known as pulse-duration modulation (PDM) or pulse-length modulation (PLM), [1] is any method of representing a signal as a rectangular wave with a varying duty cycle (and for some methods also a varying period).