nuget
Curve fitting and regression: linear, polynomial and non-linear data fitting models.
Microsoft.VisualBasic.Data.Bootstrapping.Fittings 5.0.9762.11310.
01 Namespaces
Microsoft.VisualBasic.Data.Bootstrapping
| Type | Summary | Members |
|---|---|---|
| BayesianCurveFitting | 3 | |
| DoubleLinear | 3 | |
| Evaluation | Data fitting result evaluation. | 6 |
| Extensions | 5 | |
| FeatureProjection | 1 | |
| FitResult | 线性回归结果 | 12 |
| GaussNewtonSolver | least squares fitting for general curve functions | 1 |
| IFitted | a unify interface model of linear fitting result | 4 |
| LeastSquares | Linear interpolator 曲线拟合类，只适用于线性拟合： + y = a*x + b + y = a + a1*x + a2*x^2 + ... | 5 |
| LMA | Levenberg–Marquardt algorithm In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used… | 1 |
| LOESS | ======================================================================== LOESS回归实现 ======================================================================== | 4 |
| LOESSModel | LOESS模型，存储训练数据和参数 | 4 |
| LowessFittings | 3 | |
| NonNegativeLeastSquares | NNLS Non-Negative Least-Squares algorithm | 4 |
| NumericTablePrediction | 将回归模型的预测结果写回到统一二维表 NumericTable 的标签矩阵之中， 从而可以方便地把预测值与原始的观测值放在同一张表里面进行对比。 | 3 |
| NumericTableRegressions | 回归/曲线拟合算法的统一二维表入口。 输入约定： 1. | 20 |
| StockPredict | Bayesian Curve Fitting | 2 |
| WeightedFit | 加权拟合的结果 | 9 |
| WeightedLinearRegression | An Algorithm for Weighted Linear Regression > https://www.codeproject.com/Articles/25335/An-Algorithm-for-Weighted-Linear-Regression | 2 |
Microsoft.VisualBasic.Data.Bootstrapping.GaussNewtonSolver
| Type | Summary | Members |
|---|---|---|
| FitFunction | A general curve function to fit | 0 |
Microsoft.VisualBasic.Data.Bootstrapping.LASSO
LASSO (L1 regularized) regression.
| Type | Summary | Members |
|---|---|---|
| LassoFit | This class is a container for arrays and values that are computed during computation of a lasso fit. | 15 |
| LassoFitGenerator | This implemenation is based on: Friedman, J., Hastie, T. | 10 |
| MathUtil | Utility Math functions that are used by other classes. | 5 |
Microsoft.VisualBasic.Data.Bootstrapping.LevenbergMarquardt
The Levenberg-Marquardt non-linear least squares fitting algorithm.
| Type | Summary | Members |
|---|---|---|
| JamaHelper | Created by duy on 31/1/15. | 2 |
| LmDatumError | LmDatumError is an interface for evaluating error, Jacobian matrix and Hessian matrix of a single piece of observed data | 5 |
| LmModelError | Created by duy on 20/1/15. | 4 |
| LmParamHandler | Created by duy on 18/3/15. | 1 |
| LmScalarModel | LmScalarModel is an interface for models (functions) whose ranges are single real-valued numbers | 4 |
| LmSolver | levenberg-marquardt A lightweight implementation of Levenberg-Marquardt algorithm ### Augmented normal equation (H + uI) * h = -g where: + H is the Hessian matrix… | 9 |
| LmSumError | Created by duy on 1/4/15. | 4 |
| LmSumSquaresError | Created by duy on 27/1/15. | 4 |
Microsoft.VisualBasic.Data.Bootstrapping.LMA
| Type | Summary | Members |
|---|---|---|
| FitInput | 5 |
Microsoft.VisualBasic.Data.Bootstrapping.Logistic
Logistic regression.
Microsoft.VisualBasic.Data.Bootstrapping.Multivariate
Multivariate linear regression (MLR).
| Type | Summary | Members |
|---|---|---|
| Error | 多元线性回归在单个样本点上的拟合误差记录。(The fit error of a multiple linear regression at a single sample point.) | 5 |
| LinearFittingAlgorithm | 多元线性回归拟合算法模块，提供拟合入口、特征曲线升维以及回归系数置信区间的计算。 (Multiple linear regression fitting algorithms: fit entry points, feature curve scaling, and confidence interval computation.) | 6 |
| MLRFit | Multiple linear regression.(多元线性回归) Problem of predicting appropriate values of given feature set as inputvector using supervised linear regression with multiple dimensional sa… | 11 |
| NormalEquation | 1 |