Struct OptimizationReport 

#[non_exhaustive]
pub struct OptimizationReport {
    pub strategy_name: String,
    pub total_combinations: usize,
    pub results: Vec<OptimizationResult>,
    pub best: OptimizationResult,
    pub skipped_errors: usize,
    pub convergence_curve: Vec<f64>,
    pub n_evaluations: usize,
}

Optimisation report returned by both GridSearch and BayesianSearch.

Overfitting Warning

All metrics are in-sample — the same candle data used to optimise the parameters is used to score them. In-sample results almost always overstate real-world performance.

Always validate best parameters on unseen data — use WalkForwardConfig for an unbiased out-of-sample estimate, or reserve a held-out test period.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

strategy_name: String

Name of the strategy being optimised

total_combinations: usize

Total number of successful parameter evaluations

results: Vec<OptimizationResult>

All results sorted best-first by the target metric.

Sets that fail due to insufficient data are silently skipped. In-sample only — see struct-level docs.

best: OptimizationResult

The single best result (same object as results[0]).

In-sample only — see struct-level docs.

skipped_errors: usize

Number of combinations skipped due to unexpected errors (not insufficient data). A non-zero value indicates a configuration problem.

convergence_curve: Vec<f64>

Running best metric value after each successful evaluation, in order.

BayesianSearch populates this as a non-decreasing convergence trace. GridSearch leaves it empty — parallel execution has no sequential order.

n_evaluations: usize

Total strategy evaluations attempted (including those skipped for insufficient data).

For GridSearch: equals total_combinations. For BayesianSearch: equals max_evaluations (or fewer if data is short).

Trait Implementations

impl Clone for OptimizationReport

fn clone(&self) -> OptimizationReport

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for OptimizationReport

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for OptimizationReport

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for OptimizationReport

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

where __S: Serializer,

Serialize this value into the given Serde serializer.