enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Bias–variance tradeoff - Wikipedia

    en.wikipedia.org/wiki/Biasvariance_tradeoff

    Even though the bias–variance decomposition does not directly apply in reinforcement learning, a similar tradeoff can also characterize generalization. When an agent has limited information on its environment, the suboptimality of an RL algorithm can be decomposed into the sum of two terms: a term related to an asymptotic bias and a term due ...

  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. Observer bias - Wikipedia

    en.wikipedia.org/wiki/Observer_bias

    Another key example of observer bias is a 1963 study, "Psychology of the Scientist: V. Three Experiments in Experimenter Bias", [9] published by researchers Robert Rosenthal and Kermit L. Fode at the University of North Dakota. In this study, Rosenthal and Fode gave a group of twelve psychology students a total of sixty rats to run in some ...

  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. Overfitting - Wikipedia

    en.wikipedia.org/wiki/Overfitting

    The bias–variance tradeoff is often used to overcome overfit models. With a large set of explanatory variables that actually have no relation to the dependent variable being predicted, some variables will in general be falsely found to be statistically significant and the researcher may thus retain them in the model, thereby overfitting the ...

  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. 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:

  9. Double descent - Wikipedia

    en.wikipedia.org/wiki/Double_descent

    An example of the double descent phenomenon in a two-layer neural network: ... (an extrapolation of the bias–variance tradeoff), [9] ...