sklears_feature_selection/evaluation/
statistical_testing.rs

1//! Statistical significance testing for feature selection evaluation
2//!
3//! This module provides stub implementations for statistical testing methods.
4//! Full implementations are planned for future releases.
5
6use scirs2_core::error::CoreError;
7type Result<T> = std::result::Result<T, CoreError>;
8
9/// Statistical testing framework (stub implementation)
10#[derive(Debug, Clone)]
11pub struct StatisticalTesting;
12
13impl StatisticalTesting {
14    pub fn test_significance(_features: &[usize]) -> Result<f64> {
15        // Stub implementation
16        Ok(0.05) // p-value
17    }
18}
19
20/// Permutation tests (stub implementation)
21#[derive(Debug, Clone)]
22pub struct PermutationTests;
23
24impl PermutationTests {
25    pub fn permutation_test(_features: &[usize], _n_permutations: usize) -> Result<f64> {
26        Ok(0.05)
27    }
28}
29
30/// Significance analysis (stub implementation)
31#[derive(Debug, Clone)]
32pub struct SignificanceAnalysis;
33
34impl SignificanceAnalysis {
35    pub fn analyze_significance(_features: &[usize]) -> Result<Vec<f64>> {
36        Ok(vec![0.05; _features.len()])
37    }
38}
39
40/// Multiple comparisons correction (stub implementation)
41#[derive(Debug, Clone)]
42pub struct MultipleComparisonsCorrection;
43
44impl MultipleComparisonsCorrection {
45    pub fn bonferroni_correction(_p_values: &[f64]) -> Result<Vec<f64>> {
46        Ok(_p_values.to_vec())
47    }
48
49    pub fn fdr_correction(_p_values: &[f64]) -> Result<Vec<f64>> {
50        Ok(_p_values.to_vec())
51    }
52}
53
54/// Power analysis (stub implementation)
55#[derive(Debug, Clone)]
56pub struct PowerAnalysis;
57
58impl PowerAnalysis {
59    pub fn compute_power(_effect_size: f64, _sample_size: usize) -> Result<f64> {
60        Ok(0.8)
61    }
62}
sklears_feature_selection/evaluation/statistical_testing.rs

sklears_feature_selection/evaluation/
statistical_testing.rs
