Estimates Reliability of Individual Supervised Learning
Predictions
person("Simon", "Cof", email = "simon.cof@windowslive.com", role = c("aut", "cre"))
An implementation of reliability estimation methods described in the paper (Bosnic, Z., & Kononenko, I. (2008) <doi:10.1007/s10489-007-0084-9>), which allows you to test the reliability of a single predicted instance made
by your model and prediction function. It also allows you to make a correlation test to estimate which reliability estimate is the most
accurate for your model.

Tools for Detecting Predatory Publishers and Journals
Allows the user to check and find (allegedly) predatory journals based on Beall's list available at <https://scholarlyoa.com/>.
As part of a research project, the data from the website has been scrapped with web scraping algorithms and manual work.
The package includes a search function and direct access to this database of predatory journals. The use of this tool
should facilitate the detection of predatory publications by researchers and librarians.

Allows the user to check and find (allegedly) predatory journals based on Beall's list available at <https://scholarlyoa.com/>.
As part of a research project, the data from the website has been scraped with web scraping algorithms and manual work.
The package includes a search function and direct access to this database of predatory journals. The use of this tool
should facilitate the detection of predatory publications by researchers and librarians.

Allows the user to check and find (allegedly) predatory journals based on Beall's list available at <https://scholarlyoa.com/>.
As part of a research project, the data from the website has been scraped with a web scraping script.
The package includes a search function and direct access to this database of predatory journals. The use of this tool
should facilitate the detection of predatory publications by researchers and librarians.

Classification rule based on Bayesian naive Bayes models with
feature selection bias corrected
"predict.bayes" predicts the binary response