Vanishing Point detection for images and videos using Least Squares in C++

Repository containing introduction to the main methods and models used in machine learning problems of regression, classification and clustering.

Distributed least squares approximation (dlsa) implemented with Apache Spark

Python Tools to Practically Model and Solve the Problem of High Speed Rotor Balancing.

Solve many kinds of least-squares and matrix-recovery problems

RANSAC (RANdom SAmple Consensus) Algorithm Implementation

Numerical analysis methods implemented in Python.

Trilateration example using least squares method in scipy

**curve_fit_utils** is a Python module containing useful tools for curve fitting

Robust Regression for arbitrary non-linear functions

Time Series Regression with Python

Some useful algorithms implemented in Python

A fast and low memory requirement version of PointHop and PointHop++, which is built upon Apache Spark.

Implementation of the Locally Optimized Random SAmple Consensus (LO-RANSAC) 3D plane fitting algorithm

Robust locally weighted multiple regression in Python

Machine learning library for symbolic fitting: the unknown system/function is described via NARMAX algebraic expressions being linear combinations of arbitrary non-linear terms provided by the user (like 0.2x²+0.7sin(x) or x[k-1]*y[k-4]^2).

DLTReconvolution - A Python based software for the analysis of lifetime spectra using the iterative least-square reconvolution method

Randomized Extended Kaczmarz (C++)

This is the implementation of the five regression methods Least Square (LS), Regularized Least Square (RLS), LASSO, Robust Regression (RR) and Bayesian Regression (BR).

基于.Net Framework/WPF框架开发的、通过最小二乘法实现的多项式曲线拟合软件