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  2. Bias–variance tradeoff - Wikipedia

    en.wikipedia.org/wiki/Biasvariance_tradeoff

    In artificial neural networks, the variance increases and the bias decreases as the number of hidden units increase, [12] although this classical assumption has been the subject of recent debate. [4] Like in GLMs, regularization is typically applied. In k-nearest neighbor models, a high value of k leads to high bias and low variance (see below).

  3. Occam's razor - Wikipedia

    en.wikipedia.org/wiki/Occam's_razor

    The bias–variance tradeoff is a framework that incorporates the Occam's razor principle in its balance between overfitting (associated with lower bias but higher variance) and underfitting (associated with lower variance but higher bias).

  4. List of cognitive biases - Wikipedia

    en.wikipedia.org/wiki/List_of_cognitive_biases

    In psychology and cognitive science, a memory bias is a cognitive bias that either enhances or impairs the recall of a memory (either the chances that the memory will be recalled at all, or the amount of time it takes for it to be recalled, or both), or that alters the content of a reported memory. There are many types of memory bias, including:

  5. Supervised learning - Wikipedia

    en.wikipedia.org/wiki/Supervised_learning

    But if the learning algorithm is too flexible, it will fit each training data set differently, and hence have high variance. A key aspect of many supervised learning methods is that they are able to adjust this tradeoff between bias and variance (either automatically or by providing a bias/variance parameter that the user can adjust).

  6. Cognitive bias - Wikipedia

    en.wikipedia.org/wiki/Cognitive_bias

    The Cognitive Bias Codex. A cognitive bias is a systematic pattern of deviation from norm or rationality in judgment. [1] Individuals create their own "subjective reality" from their perception of the input. An individual's construction of reality, not the objective input, may dictate their behavior in the world.

  7. Shrinkage (statistics) - Wikipedia

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

    An example arises in the estimation of the population variance by sample variance. For a sample size of n , the use of a divisor n −1 in the usual formula ( Bessel's correction ) gives an unbiased estimator, while other divisors have lower MSE, at the expense of bias.

  8. Naïve realism (psychology) - Wikipedia

    en.wikipedia.org/wiki/Naïve_realism_(psychology)

    The term, as it is used in psychology today, was coined by social psychologist Lee Ross and his colleagues in the 1990s. [ 1 ] [ 2 ] It is related to the philosophical concept of naïve realism , which is the idea that our senses allow us to perceive objects directly and without any intervening processes. [ 3 ]

  9. Choice-supportive bias - Wikipedia

    en.wikipedia.org/wiki/Choice-supportive_bias

    Choice-supportive bias or post-purchase rationalization is the tendency to retroactively ascribe positive attributes to an option one has selected and/or to demote the forgone options. [1] It is part of cognitive science, and is a distinct cognitive bias that occurs once a decision is made. For example, if a person chooses option A instead of ...