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 25 of file accuracy.hpp.

Member Function Documentation

◆ Evaluate()

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

Run classification and calculate accuracy.

Parameters
modelA classification model.
dataColumn-major data containing test items.
labelsGround truth (correct) labels for the test items.

Member Data Documentation

◆ NeedsMinimization

const bool NeedsMinimization = false
static

Information for hyper-parameter tuning code.

It indicates that we want to maximize the metric.

Definition at line 44 of file accuracy.hpp.


The documentation for this class was generated from the following file:
  • /home/ryan/src/mlpack.org/_src/mlpack-3.3.1/src/mlpack/core/cv/metrics/accuracy.hpp