Package com.jml.linear_models
package com.jml.linear_models
This package contains several linear models that can be fit to a dataset.
Linear Models:
Linear Models:
Linear Regression
Multiple Linear Regression
Polynomial Regression
Linear Regression with Stochastic Gradient Descent
Multiple Linear Regression with Stochastic Gradient Descent
Polynomial Regression with Stochastic Gradient Descent
Perceptron
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Class SummaryClassDescriptionModel for ordinary least squares linear regression of one variable.
LinearRegression fits a model y = b0 + b1x to the datasets by minimizing the residuals of the sum of squares between the values in the target dataset and the values predicted by the model.Model for least squares linear regression of one variable by stochastic gradient descent.
LinearRegressionSGD fits a model y = b0 + b1x to the datasets by minimizing the residuals of the sum of squares between the values in the target dataset and the values predicted by the model.Model for least squares linear regression of multiple variables by least squares.
MultipleLinearRegression fits a model y = b0 + b1x1 + ...Model for least squares linear regression of multiple variables by stochastic gradient descent.
MultipleLinearRegressionSGD fits a model y = b0 + b1x1 + ...A perceptron is a linear model that is equivalent to a single layer neural network.
When a perceptron model is saved, it will be saved as a neural network model.Model for least squares linear regression of polynomials.
PolynomialRegression fits a model y = b0 + b1x + b2x2 + ...Model for least squares regression of polynomials usingStochastic Gradient Descent.
PolynomialRegression fits a model y = b0 + b1x + b2x2 + ... -
Enum Class Summary