Struct TrainingRun

pub struct TrainingRun {
    pub evaluation_metrics: Option<EvaluationMetrics>,
    pub start_time: OffsetDateTime,
    pub data_split_result: Option<DataSplitResult>,
    pub training_options: Option<TrainingOptions>,
    pub global_explanations: Option<Vec<GlobalExplanation>>,
    pub results: Option<Vec<IterationResult>>,
}

Fields

evaluation_metrics: Option<EvaluationMetrics>

The evaluation metrics over training/eval data that were computed at the end of training.

start_time: OffsetDateTime

The start time of this training run.

data_split_result: Option<DataSplitResult>

Data split result of the training run. Only set when the input data is actually split.

training_options: Option<TrainingOptions>

Options that were used for this training run, includes user specified and default options that were used.

global_explanations: Option<Vec<GlobalExplanation>>

Global explanations for important features of the model. For multi-class models, there is one entry for each label class. For other models, there is only one entry in the list.

results: Option<Vec<IterationResult>>

Output of each iteration run, results.size() <= max_iterations.

Trait Implementations

impl Clone for TrainingRun

fn clone(&self) -> TrainingRun

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TrainingRun

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for TrainingRun

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for TrainingRun

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for TrainingRun

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.