ee.ConfusionMatrix.fscore
Computes the Fβ-score for the confusion matrix.
| Usage | Returns |
|---|
ConfusionMatrix.fscore(beta) | Array |
| Argument | Type | Details |
|---|
this: confusionMatrix | ConfusionMatrix | |
beta | Float, default: 1 | A factor indicating how much more important recall is than precision. The standard F-score is equivalent to setting β to one. |
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[[["Calculates the Fβ-score, a measure combining precision and recall, from a confusion matrix."],["Allows customization of the score through a `beta` parameter, weighing the importance of recall relative to precision."],["Provides flexibility by accepting the confusion matrix as input and returning the Fβ-score as an array."]]],["The `fscore` function calculates the Fβ-score for a given confusion matrix. It accepts a `beta` argument, a float value defaulting to 1, which determines the relative importance of recall versus precision. A higher `beta` emphasizes recall. The function operates on a `ConfusionMatrix` object and returns an array containing the computed Fβ-score. The standard F-score is calculated when β is set to one.\n"]]