enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Loss function - Wikipedia

    en.wikipedia.org/wiki/Loss_function

    Leonard J. Savage argued that using non-Bayesian methods such as minimax, the loss function should be based on the idea of regret, i.e., the loss associated with a decision should be the difference between the consequences of the best decision that could have been made had the underlying circumstances been known and the decision that was in fact taken before they were known.

  3. Opportunity cost - Wikipedia

    en.wikipedia.org/wiki/Opportunity_cost

    Opportunity cost, as such, is an economic concept in economic theory which is used to maximise value through better decision-making. In accounting, collecting, processing, and reporting information on activities and events that occur within an organization is referred to as the accounting cycle.

  4. Deadweight loss - Wikipedia

    en.wikipedia.org/wiki/Deadweight_loss

    Deadweight loss. In economics, deadweight loss is the loss of societal economic welfare due to production/consumption of a good at a quantity where marginal benefit (to society) does not equal marginal cost (to society) – in other words, there are either goods being produced despite the cost of doing so being larger than the benefit, or ...

  5. Sunk cost - Wikipedia

    en.wikipedia.org/wiki/Sunk_cost

    Sunk cost. In economics and business decision-making, a sunk cost (also known as retrospective cost) is a cost that has already been incurred and cannot be recovered. [1][2] Sunk costs are contrasted with prospective costs, which are future costs that may be avoided if action is taken. [3] In other words, a sunk cost is a sum paid in the past ...

  6. Cross-entropy - Wikipedia

    en.wikipedia.org/wiki/Cross-entropy

    Definition. The cross-entropy of the distribution relative to a distribution over a given set is defined as follows: , where is the expected value operator with respect to the distribution . The definition may be formulated using the Kullback–Leibler divergence , divergence of from (also known as the relative entropy of with respect to ...

  7. Loss functions for classification - Wikipedia

    en.wikipedia.org/wiki/Loss_functions_for...

    In machine learning and mathematical optimization, loss functions for classification are computationally feasible loss functions representing the price paid for inaccuracy of predictions in classification problems (problems of identifying which category a particular observation belongs to). [1] Given as the space of all possible inputs (usually ...

  8. Cost-loss model - Wikipedia

    en.wikipedia.org/wiki/Cost-loss_model

    The cost-loss model, also called the cost/loss model or the cost-loss decision model, is a model used to understand how the predicted probability of adverse events affects the decision of whether to take a costly precautionary measure to protect oneself against losses from that event. The threshold probability above which it makes sense to take ...

  9. Loss aversion - Wikipedia

    en.wikipedia.org/wiki/Loss_aversion

    A loss of $0.05 is perceived with a much greater utility loss than the utility increase of a comparable gain. Loss aversion is a psychological and economic concept, [1] which refers to how outcomes are interpreted as gains and losses where losses are subject to more sensitivity in people's responses compared to equivalent gains acquired. [2]