robotomize / regression-php
此包已被弃用且不再维护。没有建议的替代包。
计算回归
v0.3.3
2017-08-30 22:41 UTC
Requires
- php: >=7.0
- nesbot/carbon: ^1.21
- paragonie/random_compat: ^2.0
Requires (Dev)
- phpmd/phpmd: 2.*
- phpunit/phpunit: ~4.0|~5.0
- squizlabs/php_codesniffer: 2.*
This package is not auto-updated.
Last update: 2023-03-18 10:36:29 UTC
README
描述
- 回归建模的实现
- 正在开发新的回归模型
- 将为 php 5.6 开辟单独的线程
要求
- composer 依赖(Carbon DateTime, random-bytes)
-
= PHP 7.0
安装
composer require robotomize/regression-php
线性回归算法
基本用法
$testData = [[0, 10], [1, 20], [2, 3], [3, 15], [4, 0]] $linear = new LinearRegression(); $linear->setSourceSequence($testData); $linear->calculate(); /** @var RegressionModel $regressionModel */ $regressionModel = $linear->getRegressionModel();
工厂用法
/** @var RegressionModel $regressionModel */ $regressionModel = Regression::Linear([[0, 10], [1, 20], [2, 3], [3, 15], [4, 0]]);
指数回归
基本用法
$exponential = new ExponentialRegression(); $exponential->setSourceSequence($testData); $exponential->calculate(); $regressionModel = $exponential->getRegressionModel();
工厂用法
$regressionModel = Regression::Exponential($testData);
对数回归
基本用法
$logarithmic = new LogarithmicRegression(); $logarithmic->setSourceSequence($testData); $logarithmic->calculate(); /** @var RegressionModel $regressionModel */ $regressionModel = $logarithmic->getRegressionModel();
工厂用法
$regressionModel = RegressionFactory::Logarithmic($testData);
幂回归
基本用法
$powerReg = new PowerRegression(); $powerReg->setSourceSequence($testData); $powerReg->calculate(); /** @var RegressionModel $regressionModel */ $regressionModel = $powerReg->getRegressionModel();
工厂用法
$regressionModel = RegressionFactory::Power($testData);