Struct ClassificationProfiler 

pub struct ClassificationProfiler<Model, Opt, Input, Output> { /* private fields */ }

A profiler for classification models that measures training time and computes classification metrics.

This struct implements the Profiler trait specifically for classification models, providing performance assessment through metrics such as accuracy, precision, recall, and F1 score.

Type Parameters

• Model - The classification model type being profiled
• Opt - The optimizer type used for training
• Input - The input data type (features)
• Output - The output data type (labels/classes)

Implementations

impl<Model, Opt, Input, Output> ClassificationProfiler<Model, Opt, Input, Output>

pub fn new() -> Self

Creates a new ClassificationProfiler instance.

Returns

A new ClassificationProfiler instance.

Trait Implementations

impl<Model, Opt, Input, Output> Default for ClassificationProfiler<Model, Opt, Input, Output>

fn default() -> Self

Returns the “default value” for a type.

impl<Model, Opt, Input, Output> Profiler<Model, Opt, Input, Output> for ClassificationProfiler<Model, Opt, Input, Output>

where Model: BaseModel<Input, Output> + ClassificationModel<Input, Output>, Opt: Optimizer<Input, Output, Model>,

fn train( &self, model: &mut Model, optimizer: &mut Opt, x: &Input, y: &Output, ) -> Result<(TrainMetrics, Self::EvalMetrics), ProfilerError>

Profiles the training process of a classification model.

Measures the time taken to train the model and computes classification metrics on the provided data.

Arguments

• model - Mutable reference to the classification model being trained
• optimizer - Mutable reference to the optimizer used for training
• x - Reference to input features
• y - Reference to target labels

Returns

A tuple containing training metrics (including training time) and classification metrics (accuracy, precision, recall, F1 score), or a ProfilerError if an error occurs.

fn profile_evaluation( &self, model: &mut Model, x: &Input, y: &Output, ) -> Result<Self::EvalMetrics, ProfilerError>

Profiles the evaluation process of a classification model.

Computes classification metrics for the model on the provided data.

Arguments

• model - Mutable reference to the classification model being evaluated
• x - Reference to input features
• y - Reference to target labels

Returns

Classification metrics (accuracy, precision, recall, F1 score), or a ProfilerError if an error occurs.

type EvalMetrics = ClassificationMetrics

The type of evaluation metrics returned by the profiler