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Merge potential next release v0.4 (#187) Breaking Changes

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* First draft of the new n-dimensional arrays + NB use case
* Improves default implementation of multiple Array methods
* Refactors tree methods
* Adds matrix decomposition routines
* Adds matrix decomposition methods to ndarray and nalgebra bindings
* Refactoring + linear regression now uses array2
* Ridge & Linear regression
* LBFGS optimizer & logistic regression
* LBFGS optimizer & logistic regression
* Changes linear methods, metrics and model selection methods to new n-dimensional arrays
* Switches KNN and clustering algorithms to new n-d array layer
* Refactors distance metrics
* Optimizes knn and clustering methods
* Refactors metrics module
* Switches decomposition methods to n-dimensional arrays
* Linalg refactoring - cleanup rng merge (#172)
* Remove legacy DenseMatrix and BaseMatrix implementation. Port the new Number, FloatNumber and Array implementation into module structure.
* Exclude AUC metrics. Needs reimplementation
* Improve developers walkthrough

New traits system in place at `src/numbers` and `src/linalg`
Co-authored-by: Lorenzo <tunedconsulting@gmail.com>

* Provide SupervisedEstimator with a constructor to avoid explicit dynamical box allocation in 'cross_validate' and 'cross_validate_predict' as required by the use of 'dyn' as per Rust 2021
* Implement getters to use as_ref() in src/neighbors
* Implement getters to use as_ref() in src/naive_bayes
* Implement getters to use as_ref() in src/linear
* Add Clone to src/naive_bayes
* Change signature for cross_validate and other model_selection functions to abide to use of dyn in Rust 2021
* Implement ndarray-bindings. Remove FloatNumber from implementations
* Drop nalgebra-bindings support (as decided in conf-call to go for ndarray)
* Remove benches. Benches will have their own repo at smartcore-benches
* Implement SVC
* Implement SVC serialization. Move search parameters in dedicated module
* Implement SVR. Definitely too slow
* Fix compilation issues for wasm (#202)

Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
* Fix tests (#203)

* Port linalg/traits/stats.rs
* Improve methods naming
* Improve Display for DenseMatrix

Co-authored-by: Montana Low <montanalow@users.noreply.github.com>
Co-authored-by: VolodymyrOrlov <volodymyr.orlov@gmail.com>
This commit is contained in:
Lorenzo
2022-10-31 10:44:57 +00:00
committed by GitHub
parent bb71656137
commit 52eb6ce023
110 changed files with 10327 additions and 9107 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/metrics/cluster_helpers.rs
+34 -33
View File
@@ -1,12 +1,12 @@
#![allow(clippy::ptr_arg)]
use std::collections::HashMap;
use crate::math::num::RealNumber;
use crate::math::vector::RealNumberVector;
use crate::linalg::basic::arrays::ArrayView1;
use crate::numbers::basenum::Number;
pub fn contingency_matrix<T: RealNumber>(
labels_true: &Vec<T>,
labels_pred: &Vec<T>,
pub fn contingency_matrix<T: Number + Ord, V: ArrayView1<T> + ?Sized>(
labels_true: &V,
labels_pred: &V,
) -> Vec<Vec<usize>> {
let (classes, class_idx) = labels_true.unique_with_indices();
let (clusters, cluster_idx) = labels_pred.unique_with_indices();
@@ -24,28 +24,30 @@ pub fn contingency_matrix<T: RealNumber>(
contingency_matrix
}
pub fn entropy<T: RealNumber>(data: &[T]) -> Option<T> {
let mut bincounts = HashMap::with_capacity(data.len());
pub fn entropy<T: Number + Ord, V: ArrayView1<T> + ?Sized>(data: &V) -> Option<f64> {
let mut bincounts = HashMap::with_capacity(data.shape());
for e in data.iter() {
for e in data.iterator(0) {
let k = e.to_i64().unwrap();
bincounts.insert(k, bincounts.get(&k).unwrap_or(&0) + 1);
}
let mut entropy = T::zero();
let sum = T::from_usize(bincounts.values().sum()).unwrap();
let mut entropy = 0f64;
let sum: i64 = bincounts.values().sum();
for &c in bincounts.values() {
if c > 0 {
let pi = T::from_usize(c).unwrap();
entropy -= (pi / sum) * (pi.ln() - sum.ln());
let pi = c as f64;
let pi_ln = pi.ln();
let sum_ln = (sum as f64).ln();
entropy -= (pi / sum as f64) * (pi_ln - sum_ln);
}
}
Some(entropy)
}
pub fn mutual_info_score<T: RealNumber>(contingency: &[Vec<usize>]) -> T {
pub fn mutual_info_score(contingency: &[Vec<usize>]) -> f64 {
let mut contingency_sum = 0;
let mut pi = vec![0; contingency.len()];
let mut pj = vec![0; contingency[0].len()];
@@ -64,37 +66,36 @@ pub fn mutual_info_score<T: RealNumber>(contingency: &[Vec<usize>]) -> T {
}
}
let contingency_sum = T::from_usize(contingency_sum).unwrap();
let contingency_sum = contingency_sum as f64;
let contingency_sum_ln = contingency_sum.ln();
let pi_sum_l = T::from_usize(pi.iter().sum()).unwrap().ln();
let pj_sum_l = T::from_usize(pj.iter().sum()).unwrap().ln();
let pi_sum: usize = pi.iter().sum();
let pj_sum: usize = pj.iter().sum();
let pi_sum_l = (pi_sum as f64).ln();
let pj_sum_l = (pj_sum as f64).ln();
let log_contingency_nm: Vec<T> = nz_val
let log_contingency_nm: Vec<f64> = nz_val.iter().map(|v| (*v as f64).ln()).collect();
let contingency_nm: Vec<f64> = nz_val
.iter()
.map(|v| T::from_usize(*v).unwrap().ln())
.collect();
let contingency_nm: Vec<T> = nz_val
.iter()
.map(|v| T::from_usize(*v).unwrap() / contingency_sum)
.map(|v| (*v as f64) / contingency_sum)
.collect();
let outer: Vec<usize> = nzx
.iter()
.zip(nzy.iter())
.map(|(&x, &y)| pi[x] * pj[y])
.collect();
let log_outer: Vec<T> = outer
let log_outer: Vec<f64> = outer
.iter()
.map(|&o| -T::from_usize(o).unwrap().ln() + pi_sum_l + pj_sum_l)
.map(|&o| -(o as f64).ln() + pi_sum_l + pj_sum_l)
.collect();
let mut result = T::zero();
let mut result = 0f64;
for i in 0..log_outer.len() {
result += (contingency_nm[i] * (log_contingency_nm[i] - contingency_sum_ln))
+ contingency_nm[i] * log_outer[i]
}
result.max(T::zero())
result.max(0f64)
}
#[cfg(test)]
@@ -104,8 +105,8 @@ mod tests {
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn contingency_matrix_test() {
let v1 = vec![0.0, 0.0, 1.0, 1.0, 2.0, 0.0, 4.0];
let v2 = vec![1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0];
let v1 = vec![0, 0, 1, 1, 2, 0, 4];
let v2 = vec![1, 0, 0, 0, 0, 1, 0];
assert_eq!(
vec!(vec!(1, 2), vec!(2, 0), vec!(1, 0), vec!(1, 0)),
@@ -116,17 +117,17 @@ mod tests {
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn entropy_test() {
let v1 = vec![0.0, 0.0, 1.0, 1.0, 2.0, 0.0, 4.0];
let v1 = vec![0, 0, 1, 1, 2, 0, 4];
assert!((1.2770f32 - entropy(&v1).unwrap()).abs() < 1e-4);
assert!((1.2770 - entropy(&v1).unwrap() as f64).abs() < 1e-4);
}
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn mutual_info_score_test() {
let v1 = vec![0.0, 0.0, 1.0, 1.0, 2.0, 0.0, 4.0];
let v2 = vec![1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0];
let s: f32 = mutual_info_score(&contingency_matrix(&v1, &v2));
let v1 = vec![0, 0, 1, 1, 2, 0, 4];
let v2 = vec![1, 0, 0, 0, 0, 1, 0];
let s = mutual_info_score(&contingency_matrix(&v1, &v2));
assert!((0.3254 - s).abs() < 1e-4);
}