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https://github.com/ap6yc/rocketeer.jl

A Julia implementation of the Rocket method of using random feature kernels for time series classification.
https://github.com/ap6yc/rocketeer.jl

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A Julia implementation of the Rocket method of using random feature kernels for time series classification.

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README 

        
[![rocket-header](https://github.com/AP6YC/FileStorage/blob/main/Rocketeer/header.png?raw=true)][docs-dev-url]



A [Julia][julialang] implementation of the [Rocket][rocket-doi] method of using random feature kernels for time series classification.



This project is not programmed by the original authors of the original paper; please see the [Attribution](#attribution) section for more details on the original paper and software.



| **Documentation** | **Coverage** | **CI Status** | **Releases** |

|:-----------------:|:------------:|:-------------:|:-----------:|

| [![Dev][docs-dev-img]][docs-dev-url] | [![Codecov][codecov-img]][codecov-url] | [![CI Status][ci-img]][ci-url] | [![Zenodo][zenodo-img]][zenodo-url] |

| [![Stable][docs-stable-img]][docs-stable-url] | [![Coveralls][coveralls-img]][coveralls-url] | [![Documentation][doc-status-img]][doc-status-url] | [![version][version-img]][version-url] |

| **Dependents** | **Issues** | **JuliaHub Status** | **Downloads** |

| [![deps][deps-img]][deps-url] | [![GitHubIssues][issues-img]][issues-url] | [![JuliaHub][pkgeval-img]][pkgeval-url] | [![Downloads][downloads-img]][downloads-url] |



[version-img]: https://juliahub.com/docs/General/Rocketeer/stable/version.svg

[version-url]: https://juliahub.com/ui/Packages/General/Rocketeer



[deps-img]: https://juliahub.com/docs/General/Rocketeer/stable/deps.svg

[deps-url]: https://juliahub.com/ui/Packages/General/Rocketeer?t=2



[downloads-img]: https://shields.io/endpoint?url=https://pkgs.genieframework.com/api/v1/badge/Rocketeer

[downloads-url]: https://pkgs.genieframework.com?packages=Rocketeer



[issues-img]: https://img.shields.io/github/issues/AP6YC/Rocketeer.jl

[issues-url]: https://github.com/AP6YC/Rocketeer.jl/issues



[zenodo-img]: https://zenodo.org/badge/DOI/10.5281/zenodo.8197847.svg

[zenodo-url]: https://doi.org/10.5281/zenodo.8197847



[pkgeval-img]: https://juliahub.com/docs/Rocketeer/pkgeval.svg

[pkgeval-url]: https://juliahub.com/ui/Packages/Rocketeer



[docs-stable-img]: https://img.shields.io/badge/docs-stable-blue.svg

[docs-stable-url]: https://AP6YC.github.io/Rocketeer.jl/stable



[docs-dev-img]: https://img.shields.io/badge/docs-dev-blue.svg

[docs-dev-url]: https://AP6YC.github.io/Rocketeer.jl/dev



[doc-status-img]: https://github.com/AP6YC/Rocketeer.jl/actions/workflows/Documentation.yml/badge.svg

[doc-status-url]: https://github.com/AP6YC/Rocketeer.jl/actions/workflows/Documentation.yml



[ci-img]: https://github.com/AP6YC/Rocketeer.jl/workflows/CI/badge.svg

[ci-url]: https://github.com/AP6YC/Rocketeer.jl/actions?query=workflow%3ACI



[codecov-img]: https://codecov.io/gh/AP6YC/Rocketeer.jl/branch/main/graph/badge.svg

[codecov-url]: https://codecov.io/gh/AP6YC/Rocketeer.jl



[coveralls-img]: https://coveralls.io/repos/github/AP6YC/Rocketeer.jl/badge.svg?branch=main

[coveralls-url]: https://coveralls.io/github/AP6YC/Rocketeer.jl?branch=main



[julialang]: https://julialang.org/

[rocket-doi]: https://doi.org/10.1007/s10618-020-00701-z

[rocket-code]: https://github.com/angus924/rocket

[rocket-paper]: https://link.springer.com/article/10.1007/s10618-020-00701-z

[rocket-preprint]: https://arxiv.org/abs/1910.13051



## Table of Contents



- [Table of Contents](#table-of-contents)

- [Usage](#usage)

- [Attribution](#attribution)

  - [Authors](#authors)

  - [Icons](#icons)



## Usage



For detailed usage instructions, please see the [Documentation][docs-dev-url].



To use the package, you must:



1. Load `Rocketeer`,

2. Create a `RocketModule` object (with optionally specified `input_length` and `n_kernels` hyperparameters),

3. `apply_kernels` to your dataset to extract the Rocket features,

4. Optionally `save_rocket` and `load_rocket` if you intend to utilize the exact same kernels in future experiments.



For example:



```julia

# Load the module

using Rocketeer



# Set some parameters of the example

filepath = "my_rocket"  # Point to a save file

input_length = 10       # The length of the input window

n_kernels = 200         # The number of kernels to generate



# Create a rocket module

my_rocket = RocketModule(input_length, n_kernels)



# Save it for future use

save_rocket(my_rocket, filepath)



# Load the module back into a new object

my_new_rocket = load_rocket(filepath)



# Create some random data

X = rand(input_length)



# Apply the kernels to get features

features = apply_kernels(my_new_rocket, X)

```



## Attribution



### Authors



This Julia package is programmed by:



- Sasha Petrenko  [@AP6YC](https://github.com/AP6YC)



The original paper is authored by:



- Angus Dempster

- Francois Petitjean

- Geoff Webb



The links for the original work are:



- Papers:

  - [Journal article][rocket-paper] ([DOI][rocket-doi])

  - [Preprint][rocket-preprint]

- Software:

  - [rocket][rocket-code] (Python)



The bibtex entry for the original paper is:



```bibtex

@article{dempster_etal_2020,

    author  = {Dempster, Angus and Petitjean, Francois and Webb, Geoffrey I},

    title   = {ROCKET: Exceptionally fast and accurate time classification using random convolutional kernels},

    year    = {2020},

    journal = {Data Mining and Knowledge Discovery},

    doi     = {https://doi.org/10.1007/s10618-020-00701-z}

}

```



### Icons



The icon used for the project logo is from the following:



- [Space shuttle icons created by Freepik - Flaticon](https://www.flaticon.com/free-icons/space-shuttle) ([startup_1067357](https://www.flaticon.com/free-icon/startup_1067357))