Classification analysis

Create and save classification model or load classification model for prediction of classes or cross-validation of classification model

Classification mode – Select classification mode
Classification type – Select classification type
Are covariance matrices equal? – Are covariance matrices (within classes/groups/clusters) equal?
Path to table with data matrix – Path to table with data matrix
Variable names – Select variable names
Classifier name – Select classifier name: classifier consists of names of classes (samples, groups, clusters)
Path to folder with saved model – Path to folder with saved model
Percentage of data for training – Percentage of input data set (this part of input data set will be used as training set)
Path to output folder – Output folder will be created under this location when it doesn't exist