Fit-o-mat - a versatile program for nonlinear least-squares fitting
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Updated
May 6, 2024
Fit-o-mat - a versatile program for nonlinear least-squares fitting
Fitting data using a polynomial obtained by the Least Squares Method
Mileage Per Gallon (MPG) dataset based LSM linear regression model
Robust locally weighted multiple regression in Python
Explore Python implementations of predictive modeling techniques like F-test, t-test, ANOVA, linear square estimation, autocorrelation, and least squares in this practical-driven GitHub repository
KCL and KVL for the bridge circuit
KCL and KVL for the bridge circuit
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).
Jump Predictive Least Squares for Online Feature Selection
Jump Predictive Least Squares for Online Feature Selection
This project is an implementation of various machine learning algorithms (regression, classification, clustering, etc.).
Time Series Regression with Python
Example of solving least square problem with python
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
A set of codes in MATLAB for ODE reconstruction using least-square method
Distributed least squares approximation (dlsa) implemented with Apache Spark
Utilizing attributes within the Boston Housing dataset, the project applies linear regression to predict house prices by optimizing the loss function using the method of least squares.
Finding linear equations coefficients using least squares method
Solve many kinds of least-squares and matrix-recovery problems
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