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  2. Bias–variance tradeoff - Wikipedia

    en.wikipedia.org/wiki/Bias–variance_tradeoff

    [14] [15] For example, boosting combines many "weak" (high bias) models in an ensemble that has lower bias than the individual models, while bagging combines "strong" learners in a way that reduces their variance. Model validation methods such as cross-validation (statistics) can be used to tune models so as to optimize the trade-off.

  3. Trade-off - Wikipedia

    en.wikipedia.org/wiki/Trade-off

    In economics a trade-off is expressed in terms of the opportunity cost of a particular choice, which is the loss of the most preferred alternative given up. [2] A tradeoff, then, involves a sacrifice that must be made to obtain a certain product, service, or experience, rather than others that could be made or obtained using the same required resources.

  4. Overfitting - Wikipedia

    en.wikipedia.org/wiki/Overfitting

    A sign of underfitting is that there is a high bias and low variance detected in the current model or algorithm used (the inverse of overfitting: low bias and high variance). This can be gathered from the Bias-variance tradeoff, which is the

  5. Williamson tradeoff model - Wikipedia

    en.wikipedia.org/wiki/Williamson_tradeoff_model

    The Williamson tradeoff model is a theoretical model in the economics of industrial organization which emphasizes the tradeoff associated with horizontal mergers between gains resulting from lower costs of production and the losses associated with higher prices due to greater degree of monopoly power.

  6. High-dimensional statistics - Wikipedia

    en.wikipedia.org/wiki/High-dimensional_statistics

    Indeed, the James-Stein estimator [5] provided the insight that in high-dimensional settings, one may obtain improved estimation performance through shrinkage, which reduces variance at the expense of introducing a small amount of bias. This bias-variance tradeoff was further exploited in the context of high-dimensional linear models by Hoerl ...

  7. Variational Bayesian methods - Wikipedia

    en.wikipedia.org/wiki/Variational_Bayesian_methods

    Variational Bayesian methods are a family of techniques for approximating intractable integrals arising in Bayesian inference and machine learning.They are typically used in complex statistical models consisting of observed variables (usually termed "data") as well as unknown parameters and latent variables, with various sorts of relationships among the three types of random variables, as ...

  8. Guns versus butter model - Wikipedia

    en.wikipedia.org/wiki/Guns_versus_butter_model

    The government will have to decide which balance of guns versus butter best fulfills its needs, with its choice being partly influenced by the military spending and military stance of potential opponents. Researchers in political economy have viewed the trade-off between military and consumer spending as a useful predictor of election success. [1]

  9. Flexibility–usability tradeoff - Wikipedia

    en.wikipedia.org/wiki/Flexibility–usability...

    The tradeoff exists because accommodating flexibility requires satisfying a larger set of requirements, which results in complexity and usability compromises. [ 1 ] Design theory maintains that over their lifecycle, systems shift from supporting multiple uses inefficiently, towards efficiently supporting a single use as users' needs become more ...