mlpack::cv::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...

#include <accuracy.hpp>

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.

Member Function Documentation

Evaluate()

template<typename MLAlgorithm , typename DataType >

double mlpack::cv::Accuracy::Evaluate ( MLAlgorithm &  model, const DataType &  data, const arma::Row< size_t > &  labels  )

static

Run classification and calculate accuracy.

Parameters

model	A classification model.
data	Column-major data containing test items.
labels	Ground truth (correct) labels for the test items.

Member Data Documentation

NeedsMinimization

const bool mlpack::cv::Accuracy::NeedsMinimization = false

static

Information for hyper-parameter tuning code.

It indicates that we want to maximize the metric.

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The documentation for this class was generated from the following files:

• src/mlpack/core/cv/metrics/accuracy.hpp
• src/mlpack/core/cv/metrics/accuracy_impl.hpp