This package was removed from CRAN on 2022-04-27. Its history is shown below.

Reason: check issues were not corrected in time. length > 1 in && or ||

Details below reflect version 3.0, its last release before removal.

gradDescent

3.0

Gradient Descent for Regression Tasks

0packages depend

–downloads / year

–test coverage

–checks pass

Overview

About

Maintained by Lala Septem Riza3 releasesCRAN page ↗GitHub ↗

An implementation of various learning algorithms based on Gradient Descent for dealing with regression tasks. The variants of gradient descent algorithm are : Mini-Batch Gradient Descent (MBGD), which is an optimization to use training data partially to reduce the computation load. Stochastic Gradient Descent (SGD), which is an optimization to use a random data in learning to reduce the computation load drastically. Stochastic Average Gradient (SAG), which is a SGD-based algorithm to minimize stochastic step to average. Momentum Gradient Descent (MGD), which is an optimization to speed-up gradient descent learning. Accelerated Gradient Descent (AGD), which is an optimization to accelerate gradient descent learning. Adagrad, which is a gradient-descent-based algorithm that accumulate previous cost to do adaptive learning. Adadelta, which is a gradient-descent-based algorithm that use hessian approximation to do adaptive learning. RMSprop, which is a gradient-descent-based algorithm that combine Adagrad and Adadelta adaptive learning ability. Adam, which is a gradient-descent-based algorithm that mean and variance moment to do adaptive learning. Stochastic Variance Reduce Gradient (SVRG), which is an optimization SGD-based algorithm to accelerates the process toward converging by reducing the gradient. Semi Stochastic Gradient Descent (SSGD),which is a SGD-based algorithm that combine GD and SGD to accelerates the process toward converging by choosing one of the gradients at a time. Stochastic Recursive Gradient Algorithm (SARAH), which is an optimization algorithm similarly SVRG to accelerates the process toward converging by accumulated stochastic information. Stochastic Recursive Gradient Algorithm+ (SARAHPlus), which is a SARAH practical variant algorithm to accelerates the process toward converging provides a possibility of earlier termination.

Install

R (source archive)pak (dev)Ubuntu (r2u)openSUSE (OBS)

url <- "https://cran.r-project.org/src/contrib/Archive/gradDescent/gradDescent_3.0.tar.gz"
pkgFile <- "gradDescent_3.0.tar.gz"
download.file(url, pkgFile)
install.packages(pkgFile, type = "source", repos = NULL)

This package is no longer on CRAN, so install.packages() cannot fetch it by name. This downloads the last archived source (3.0) and builds it locally. Install its dependencies first, and note that building from source needs the usual compiler toolchain.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("drizzersilverberg/gradDescentR")

Development version from drizzersilverberg/gradDescentR. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-graddescent

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-gradDescent

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

CRAN check results are not tracked yet.

Code health

None

Tests · ratio 0.00

not tracked

Coverage

100%

Documentation · exports

Dependencies · direct

Documentation

READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 100%
References docs: 63%

Downloads

Releases R versions

Daily download trend is not available in this view yet.

Compare downloads with other packages →

Also on17 r2u17 autocran840 conda_forge69 c2d4u

Dependencies

Declared dependencies

0 external dependencies (excludes base and recommended)

Depends (0)

none

Imports (0)

none

LinkingTo (0)

none

Suggests (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

–indirect (not tracked)

Nothing depends on this yet.

Code & Tests

Code Composition

R 2,172 (62%)Rd 1,344 (38%)

Code characteristics

Object systems

S31

Cyclomatic complexity: 3.0 median / 18 max

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

29 22 exported

Complexity

3.5 avg / 18 max

Call network

29 nodes / 39 edges

Test coverage has not been measured for this package yet; nodes fall back to a neutral fill.

Call graph

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Lowest coverage

Per-function coverage is not measured for this package yet.

People & History

People (6)

Other (6)

Galih Praja Wijaya

Contributor · added in 3.0

Dendi Handian

Contributor

Imam Fachmi Nasrulloh

Contributor

Lala Septem Riza

Contributor

Rani Megasari

Contributor · added in 3.0

Enjun Junaeti

Contributor · added in 3.0

Listed in earlier versions (1)

and Rani Megasari

no longer listed · 2.0

Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.3.0 released · 2023-04-21
archivedRemoved from CRAN
2022-04-27
check issues were not corrected in time length > 1 in && or ||
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
R
R 3.5.0 released · 2018-04-23
3.0
2018-01-25 · diff ↗
R
R 3.4.0 released · 2017-04-21
2.0.1
2017-03-11 · diff ↗
2.0
2016-12-29
R
R 3.3.0 released · 2016-05-03

Package metadata

Total releases: 3
License: GPL (>= 2) | file LICENSE OSI
Bundled data: 24 KB / 1 file
Download size: not tracked yet
Installed size: not tracked yet
With dependencies: not tracked yet

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