Accuracy Class Reference
The Accuracy is a metric of performance for classification algorithms that is equal to a proportion of correctly labeled test items among all ones for given test items. More...
Static Public Member Functions | |
template < typename MLAlgorithm , typename DataType > | |
| static double | Evaluate (MLAlgorithm &model, const DataType &data, const arma::Row< size_t > &labels) |
| Run classification and calculate accuracy. More... | |
Static Public Attributes | |
| static const bool | NeedsMinimization = false |
| Information for hyper-parameter tuning code. More... | |
Detailed Description
The Accuracy is a metric of performance for classification algorithms that is equal to a proportion of correctly labeled test items among all ones for given test items.
Definition at line 26 of file accuracy.hpp.
Member Function Documentation
◆ Evaluate()
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static |
Run classification and calculate accuracy.
- Parameters
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model A classification model. data Column-major data containing test items. labels Ground truth (correct) labels for the test items.
Member Data Documentation
◆ NeedsMinimization
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static |
Information for hyper-parameter tuning code.
It indicates that we want to maximize the metric.
Definition at line 45 of file accuracy.hpp.
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/core/cv/metrics/accuracy.hpp