classiFunc v0.1.1
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Classification of Functional Data
Efficient implementation of k-nearest neighbor estimation and kernel estimation for functional data classification.
Readme
classiFunc
Overview
The classiFunc package implements methods for functional data classification. The main functions of this package are classiKnn, a k nearest neighbor estimator for functional data, and classiKernel, a kernel estimator for functional data. The package uses efficiently implemented semimetrics to create the distance matrix of the functional observations in the function computeDistMat.
Using classiFunc
For installation instructions, see below. A hands on introduction to can be found in the vignette. Details on specific functions are in the reference manual.
Issues & Feature Requests
For issues, bugs, feature requests etc. please use the Github Issues. Input is always welcome.
Installation
You can install the current classiFunc version from CRAN with:
install.packages("classiFunc")
or the latest patched version from Github with:
# install.packages("devtools")
devtools::install_github("maierhofert/classiFunc")
Functions in classiFunc
| Name | Description | |
| DTI | Diffusion Tensor Imaging: tract profiles and outcomes | |
| DTI_original | Diffusion Tensor Imaging: tract profiles and outcomes | |
| Growth | Berkeley Growth Study Data (regular grid) | |
| Growth_irregular | Berkeley Growth Study Data | |
| classiKernel | Create a kernel estimator for functional data classification | |
| kerChoices | List the names of all implemented kernel functions | |
| metricChoices | List the names of all metrics | |
| classiFunc | The classiFunc package | |
| Phoneme | Phonetic Time Series. | |
| ArrowHead | The shape of arrow heads. | |
| BeetleFly | Beetle/Fly Data | |
| classiKnn | Create a knn estimator for functional data classification. | |
| computeDistMat | Compute a distance matrix for functional observations | |
| parallelComputeDistMat | Paralleize computing a distance matrix for functional observations | |
| predict.classiKernel | predict a classiKernel object | |
| fdataTransform | Create a preprocessing pipeline function | |
| predict.classiKnn | predict a classiKnn object | |
| No Results! | ||
Vignettes of classiFunc
| Name | ||
| classiFunc.Rmd | ||
| No Results! | ||
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Details
| Type | Package |
| Date | 2018-03-29 |
| URL | https://github.com/maierhofert/classiFunc |
| License | GPL-3 |
| Encoding | UTF-8 |
| LazyData | true |
| RoxygenNote | 6.0.1 |
| VignetteBuilder | knitr |
| NeedsCompilation | no |
| Packaged | 2018-04-16 17:02:11 UTC; tmaierhofer |
| Repository | CRAN |
| Date/Publication | 2018-04-16 17:15:34 UTC |
| imports | BBmisc (>= 1.11) , checkmate (>= 1.8.2) , dtw , fda , fda.usc , fdasrvf , proxy , rucrdtw , stats , zoo |
| suggests | knitr , parallelMap , rmarkdown , testthat |
| depends | R (>= 2.10) |
| Contributors | Karen Fuchs, Florian Pfisterer |
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