loss function oor Spaans

loss function

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A function which expresses numerically the loss produced by a decision or other event

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Función de pérdida

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Here we only list a few commonly used loss functions and their associated Bayes estimates.
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The loss function of Taguchi better illustrates this concept.
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Another popular loss function is the absolute value of the prediction error, et1.
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What is the value of k, the cost coefficient, in the Taguchi loss function?
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Would you advocate using Taguchi methods (such as loss functions) on this type of component?
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L(u, ␲) is called the loss function.
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36.31 What is a Taguchi loss function?
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Taguchi methods — statistical oriented methods including quality robustness, quality loss function, and target specifications.
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Taguchi Quality Loss Function (Appendix) Marlon Audio Company manufactures cassette tapes.
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L(z) Normalized loss function.
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Using the Taguchi loss function, an average loss per unit is computed to be $15 per unit.
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Determine the Taguchi loss function and the payback period for the investment.
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Botanical extracts with weight loss functionality sold as an integral component of dietary supplements for human consumption
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Bayesian Procedures 291 Zellner (1971) describes the optimal Bayesian estimator under other loss functions.
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Compute the value of k in the Taguchi loss function. 2.
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Determine the Bayes estimator under the absoluteerror loss function.
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Figure 5.16 shows Taguchi’s quality loss function schematically.
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When the demand is normally distributed, n(R) is computed by using the standardized loss function.
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Ingredients for use in the manufacture of dietary supplements for human consumption with weight loss functionality
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Describe the Taguchi quality loss function, and relate it to robust quality. 5.
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Lehmann in [4] has generalised the notion of the unbiased estimator with respect to the assumed loss function.
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Dietary supplements for human consumption with weight loss functionality
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The squared forecast error is an example of a loss function.
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In this section, we introduce another loss function as follows.
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Another difficulty is that the loss function may have many local minima.
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