문서

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비선형 모델

다중 예측 변수를 사용하는 비선형 회귀

클래스

NonLinearModel Nonlinear regression model class

함수

`fitnlm`	비선형 회귀 모델 피팅
`disp`	Display nonlinear regression model
`feval`	Evaluate nonlinear regression model prediction
`predict`	Predict response of nonlinear regression model
`random`	Simulate responses for nonlinear regression model

`dummyvar`	Create dummy variables
`hougen`	Hougen-Watson model
`plotPartialDependence`	Create partial dependence plot (PDP) and individual conditional expectation (ICE) plots
`statset`	Create statistics options structure
`statget`	Access values in statistics options structure

`nlinfit`	비선형 회귀
`nlintool`	Interactive nonlinear regression
`nlparci`	Nonlinear regression parameter confidence intervals
`nlpredci`	Nonlinear regression prediction confidence intervals

예제 및 방법

Nonlinear Regression Workflow

Import data, fit a nonlinear regression, test its quality, modify it to improve the quality, and make predictions based on the model.

가중 비선형 회귀

이 예제에서는 상수가 아닌 오차 분산을 갖는 데이터에 비선형 회귀 모델을 피팅하는 방법을 보여줍니다.

Pitfalls in Fitting Nonlinear Models by Transforming to Linearity

This example shows pitfalls that can occur when fitting a nonlinear model by transforming to linearity.

Nonlinear Logistic Regression

This example shows two ways of fitting a nonlinear logistic regression model.

개념

Nonlinear Regression

Parametric nonlinear models represent the relationship between a continuous response variable and one or more continuous predictor variables.

Statistics and Machine Learning Toolbox 문서

지원

Mastering Machine Learning: A Step-by-Step Guide with MATLAB

Mastering Machine Learning: A Step-by-Step Guide with MATLAB