Find out who maintains the packages you use in
             your current session or in your package library and
             maybe say 'thank you'.

A tool for starring GitHub repositories.

Consolidates and calculates different sets of time-series features from multiple
    'R' and 'Python' packages including 'Rcatch22' Henderson, T. (2021) <doi:10.5281/zenodo.5546815>,
    'feasts' O'Hara-Wild, M., Hyndman, R., and Wang, E. (2021) <https://CRAN.R-project.org/package=feasts>,
    'tsfeatures' Hyndman, R., Kang, Y., Montero-Manso, P., Talagala, T., Wang, E., Yang, Y., and O'Hara-Wild, M. (2020)
    <https://CRAN.R-project.org/package=tsfeatures>, 'tsfresh' Christ, M., Braun, N., Neuffer, J.,
    and Kempa-Liehr A.W. (2018) <doi:10.1016/j.neucom.2018.03.067>, 'TSFEL' Barandas, M., et al. (2020)
    <doi:10.1016/j.softx.2020.100456>, and 'Kats' Facebook Infrastructure Data Science (2021)
    <https://facebookresearch.github.io/Kats/>.

Provides a suite of functions for analysing, interpreting, and visualising
    time-series features calculated from different feature sets from the 'theft' package. 
    Implements statistical learning methodologies described in Henderson, T., 
    Bryant, A., and Fulcher, B. (2023) <doi:10.48550/arXiv.2303.17809>.

Provides a simple interface to search available data provided by
    Theia (<https://theia.cnes.fr>), download it, and manage it. Data can be downloaded
    based on a search result or from a cart file downloaded from Theia website.

Theme 'ggplot2', 'lattice', and 'base' graphics based on a
    few choices, including foreground color, background color, accent
    color, and font family. Fonts that aren't available on the system, but
    are available via download on 'Google Fonts', can be automatically
    downloaded, cached, and registered for use with the 'showtext' and
    'ragg' packages.

A dataset with an uneven number of cases in each class is
    said to be unbalanced. Many models produce a subpar performance on
    unbalanced datasets. A dataset can be balanced by increasing the
    number of minority cases using SMOTE 2011 <arXiv:1106.1813>,
    BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008
    <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the
    number of majority cases using NearMiss 2003
    <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek
    link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.