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  2. Loss functions for classification - Wikipedia

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

    Given the binary nature of classification, a natural selection for a loss function (assuming equal cost for false positives and false negatives) would be the 0-1 loss function (0–1 indicator function), which takes the value of 0 if the predicted classification equals that of the true class or a 1 if the predicted classification does not match ...

  3. LightGBM - Wikipedia

    en.wikipedia.org/wiki/LightGBM

    LightGBM has many of XGBoost's advantages, including sparse optimization, parallel training, multiple loss functions, regularization, bagging, and early stopping. A major difference between the two lies in the construction of trees.

  4. Huber loss - Wikipedia

    en.wikipedia.org/wiki/Huber_loss

    Two very commonly used loss functions are the squared loss, () =, and the absolute loss, () = | |.The squared loss function results in an arithmetic mean-unbiased estimator, and the absolute-value loss function results in a median-unbiased estimator (in the one-dimensional case, and a geometric median-unbiased estimator for the multi-dimensional case).

  5. Loss function - Wikipedia

    en.wikipedia.org/wiki/Loss_function

    In many applications, objective functions, including loss functions as a particular case, are determined by the problem formulation. In other situations, the decision maker’s preference must be elicited and represented by a scalar-valued function (called also utility function) in a form suitable for optimization — the problem that Ragnar Frisch has highlighted in his Nobel Prize lecture. [4]

  6. Category:Loss functions - Wikipedia

    en.wikipedia.org/wiki/Category:Loss_functions

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  7. Neptune Technologies (NEPT) Reports Q1 Loss, Misses Revenue ...

    www.aol.com/news/neptune-technologies-nept...

    Neptune Tech (NEPT) delivered earnings and revenue surprises of -80.00% and -0.57%, respectively, for the quarter ended June 2020. Do the numbers hold clues to what lies ahead for the stock?

  8. Stochastic gradient descent - Wikipedia

    en.wikipedia.org/wiki/Stochastic_gradient_descent

    There, () is the value of the loss function at -th example, and () is the empirical risk. When used to minimize the above function, a standard (or "batch") gradient descent method would perform the following iterations: w := w − η ∇ Q ( w ) = w − η n ∑ i = 1 n ∇ Q i ( w ) . {\displaystyle w:=w-\eta \,\nabla Q(w)=w-{\frac {\eta }{n ...

  9. Neptune Wellness (NEPT) Reports Q2 Loss, Tops Revenue ... - AOL

    www.aol.com/news/neptune-wellness-nept-reports-q...

    Neptune Wellness (NEPT) delivered earnings and revenue surprises of 0.00% and 13.70%, respectively, for the quarter ended September 2021. Do the numbers hold clues to what lies ahead for the stock?