sklears-decomposition 0.2.0

Matrix decomposition algorithms for sklears: PCA, ICA, NMF, SVD
Documentation 
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//! Linear algebra utilities for dictionary learning

use scirs2_core::ndarray::Array2;
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
use sklears_core::{error::Result, types::Float};

/// Least squares solver
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LeastSquaresSolver;

/// Linear system solver
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LinearSystemSolver;

/// Matrix factorization utilities
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct MatrixFactorization;

/// Cholesky decomposition
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct CholeskyDecomposition;

/// QR decomposition
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct QRDecomposition;

/// SVD decomposition
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct SVDDecomposition;

impl LeastSquaresSolver {
    pub fn solve(&self, a: &Array2<Float>, b: &Array2<Float>) -> Result<Array2<Float>> {
        // Placeholder implementation
        Ok(Array2::zeros((a.ncols(), b.ncols())))
    }
}

impl LinearSystemSolver {
    pub fn solve(&self, a: &Array2<Float>, b: &Array2<Float>) -> Result<Array2<Float>> {
        // Placeholder implementation
        Ok(Array2::zeros((a.ncols(), b.ncols())))
    }
}