MSclassifier

MSclassifier
MSclassifier classifies instances using median-supplement machine learning methods. It derives median-supplement data from a set of instances and then infer a Naive Bayes/Random Forest classifier. The resulting model predicts classes of new instances of samples. These methods are applied to binary classification problems. The median-supplement approaches to machine learning were first used to decipher hormone and HER2 receptor status phenotypes in breast cancer. It is applicable to the prediction of subcellular localization of proteins and other supervised learning problems.

Installation
The package can be installed via the R Console or the command line of a terminal.
1 Click here to download the MSclassifier package.

2. Extract the compressed downloaded file. In a linux terminal, this can be done with the line:

unzip *.zip

3. Set your working directory to the path that contains the uncompressed folder.
4. To install via the R console, start R and run the following commands:

library(devtools)   # Ensure devtools is installed in the R package
install("MSclassifier")

Alternative to step 4, the package can be installed via the command line of linux using:

R CMD INSTALL './MSclassifier'

Details

Packaged Archives

References
1. Adabor, E.S., Acquaah-Mensah, G., Mazandu, GK. (2020). MSclassifier: median-supplement model-based classification tool for automated knowledge discovery. F1000Research 9 (1114),1114 https://doi.org/10.12688/f1000research.25501.1

2. Adabor, E.S., Acquaah-Mensah, G. (2017). Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer. Briefings in Bioinformatics (2019),20(2):504-514.https://doi.org/10.1093/bib/bbx138.