caTools

caTools: Tools: moving window statistics, GIF, Base64, ROC AUC, etc. Contains several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off-error-free sum and cumsum, etc.

Keywords for this software

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References in zbMATH (referenced in 7 articles )

Showing results 1 to 7 of 7.
Sorted by year (citations)

  1. Conde, David; Fernández, Miguel A.; Rueda, Cristina; Salvador, Bonifacio: Isotonic boosting classification rules (2021)
  2. Chu, Jianghao; Lee, Tae-Hwy; Ullah, Aman: Component-wise AdaBoost algorithms for high-dimensional binary classification and class probability prediction (2020)
  3. Muschelli, John III: ROC and AUC with a binary predictor: a potentially misleading metric (2020)
  4. Ramasubramanian, Karthik; Singh, Abhishek: Machine learning using R. With time series and industry-based use cases in R (2019)
  5. Xin Wei: PROC_R: A SAS Macro that Enables Native R Programming in the Base SAS Environment (2012) not zbMATH
  6. Williams, Graham: Data Mining with Rattle and R. The art of excavating data for knowledge discovery. (2011)
  7. Elizabeth Freeman; Gretchen Moisen: PresenceAbsence: An R Package for Presence Absence Analysis (2008) not zbMATH