For classification, this is the main class for the MLSeq package.
Objects from the Class
Objects can be created by calls of the form new("ClassifySeq", ...).
This type of objects is created as a result of classify function of MLSeq package. It is then used in predictClassify function for predicting the class labels of new samples.
Slots
method:
stores the name of used classification method in the classification model
deseqTransform:
stores the name of used transformation method in the classification model
normalization:
stores the name of used normalization method in the classification model
confusionMat:
stores the information of classification performance results
trained:
stores the information about training process and model parameters that used in the corresponding model
ref
stores user defined reference class
Note
An MLSeq class stores the results of classify function and offers further slots that are populated during the analysis. The slot confusionMat stores the information of classification performance results. These results contain the classification table and several statistical measures including accuracy rate, sensitivity, specifity, positive and negative predictive rates, etc. method, normalization and deseqTransform slots store the name of used classification method, normalization method and transformation method in the classification model respectively. Lastly, the slot trained stores the information about training process and model parameters that used in the corresponding model.