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normaliser

R package for rescaling numerical vectors and time-series features.

https://github.com/hendersontrent/normaliser

Science Score: 13.0%

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    Low similarity (12.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

R package for rescaling numerical vectors and time-series features.

Basic Info
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created over 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License

README.Rmd 

---
output: rmarkdown::github_document
---

# normaliseR 

[![CRAN version](https://www.r-pkg.org/badges/version/normaliseR)](https://www.r-pkg.org/pkg/normaliseR)
[![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/normaliseR)](https://www.r-pkg.org/pkg/normaliseR)

Re-Scale Vectors and Time-Series Features

```{r, include = FALSE}
knitr::opts_chunk$set(
comment = NA, fig.width = 12, fig.height = 8, cache = FALSE)
```

## Installation

You can install the stable version of `normaliseR` from CRAN:

```{r eval = FALSE}
install.packages("normaliseR")
```

You can install the development version of `normaliseR` from GitHub using the following:

```{r eval = FALSE}
devtools::install_github("hendersontrent/normaliseR")
```

## General purpose

`normaliseR` is a software package for R for rescaling numerical vectors or `feature_calculations` objects produced by the [`theft`](https://github.com/hendersontrent/theft) R package for computing time-series features.

Putting calculated feature vectors on an equal scale is crucial for any statistical or machine learning model as variables with high variance can adversely impact the model's capacity to fit the data appropriately, learn appropriate weight values, or minimise a loss function. `normaliseR` includes function `normalise` (or `normalize`) to rescale either a whole `feature_calculations` object, or a single vector of values. The following normalisation methods are currently offered:

* z-score---`"zScore"`
* Sigmoid---`"Sigmoid"`
* Outlier-robust Sigmoid (credit to Ben Fulcher for creating the original [MATLAB version](https://github.com/benfulcher/hctsa)) -- `"RobustSigmoid"`
* Min-max---`"MinMax"`
* Maximum absolute---`"MaxAbs"`

Owner

  • Name: Trent Henderson
  • Login: hendersontrent
  • Kind: user
  • Location: Canberra, Australia
  • Company: Nous Group

Senior data scientist and statistics PhD student. Mostly coding in R, Julia, and Stan. Interested in genetic programming, time series, and data vis

GitHub Events

Total
Last Year

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 7
  • Total Committers: 1
  • Avg Commits per committer: 7.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Trent t****1@o****m 7

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 0
  • Total pull requests: 5
  • Average time to close issues: N/A
  • Average time to close pull requests: less than a minute
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • hendersontrent (6)
Top Labels
Issue Labels
Pull Request Labels
documentation (2) enhancement (1)

Packages

  • Total packages: 1
  • Total downloads:
    • cran 567 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
cran.r-project.org: normaliseR

Re-Scale Vectors and Time-Series Features

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 567 Last month
Rankings
Dependent packages count: 28.1%
Dependent repos count: 36.1%
Average: 49.7%
Downloads: 85.0%
Maintainers (1)
then6675@uni.sydney.edu.au
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • dplyr * imports
  • rlang * imports
  • scales * imports
  • stats * imports
  • knitr * suggests
  • markdown * suggests
  • pkgdown * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests