Struct DataValidator 

pub struct DataValidator;

Re-exported validation utilities.

This includes validators for data integrity, parameter constraints, and common model hyperparameter validation. Validator for input data integrity.

Provides methods to check data quality including finiteness, positivity, dimensional consistency, and target value validity.

Implementations

impl DataValidator

pub fn new() -> Self

Creates a new data validator.

pub fn check_finite(&self, values: &[f64]) -> ValidationResult<()>

Checks that all values in a slice are finite (not NaN, Inf, or -Inf).

Arguments

• values - Slice of values to check

Returns

Ok(()) if all values are finite, Err(ValidationError::NonFiniteValue) otherwise

pub fn check_positive(&self, values: &[f64]) -> ValidationResult<()>

Checks that all values are positive (> 0.0).

Arguments

• values - Slice of values to check

Returns

Ok(()) if all values are positive, Err otherwise

pub fn check_probability(&self, values: &[f64]) -> ValidationResult<()>

Checks that all values are valid probabilities (in [0, 1]).

Arguments

• values - Slice of values to check

Returns

Ok(()) if all values are valid probabilities, Err otherwise

pub fn validate_features( &self, n_samples: usize, n_features: usize, feature_names: Option<&[String]>, ) -> ValidationResult<()>

Validates feature matrix dimensions and optional feature names.

Arguments

• n_samples - Number of samples (must be > 0)
• n_features - Number of features (must be > 0)
• feature_names - Optional slice of feature names (length must match n_features)

Returns

Ok(()) if dimensions are valid, Err otherwise

pub fn validate_targets( &self, targets: &[f64], is_classification: bool, ) -> ValidationResult<()>

Validates target values for regression or classification.

Arguments

• targets - Target values to validate
• is_classification - Whether this is a classification problem

Returns

Ok(()) if targets are valid, Err otherwise

Behavior

• For classification: targets must be 0.0 or 1.0
• For regression: targets must be finite (no other constraints)

pub fn assert_same_length(&self, a: &[f64], b: &[f64]) -> ValidationResult<()>

Asserts that two slices have the same length.

Arguments

• a - First slice
• b - Second slice

Returns

Ok(()) if lengths match, Err(ValidationError::DimensionMismatch) otherwise

pub fn assert_non_empty(&self, values: &[f64]) -> ValidationResult<()>

Asserts that a slice is not empty.

Arguments

• values - Slice to check

Returns

Ok(()) if non-empty, Err(ValidationError::EmptyData) otherwise

Trait Implementations

impl Default for DataValidator

fn default() -> Self

Returns the “default value” for a type.