"Improving machine learning detection of Alzheimer disease using enhanced Manta Ray gene selection of Alzheimer gene expression datasets" 

1. Description: 
The source code of this study is divided into three main files. The "main.py" is the main file, where multiple algorithmic settings can be changed such as maxIteration, popSize, and classification model (model = 1 = SVM, model = 2 = RF, model = 3 = NB, model = 4 = XG). The  "MRFO_.py" file is the original Manta Ray Optimization Algorithm source code. The third file is  "MRFO.py" file, the improved MRFO with SRM and Improved SpaceBound function. 
2. Datasets and Usage instruction:
All datasets examined in the study are given in csv file format, please download all the files including the datasets in the same project folder, then extract the .rar files. To test a dataset, change the variable value filename = "" in main.py to appropriate dataset name (be aware to remove .csv when given the name). The default popSize is set to 50, and maxIteration is set to 100, with default model is set to 1 (SVM).
3. Dependencies: 
Make sure to use pip in your python environment and install scikitplot, sklearn, matplotlib, and xgboost libraries installed. 

NOTE: all metrics such as fitness convergence, minimum and maximum number of features selected in each iteration, evaluation metrics, minimum and maximum fitness values; are automatically stored at the end of optimization cycle. The file name will be the dataset name followed by classifier name, and ends with ".output".