For classification, this is the main class for the
MLSeq package. It contains all the information including trained model,
selected genes, cross-validation results, etc.
Objects can be created by calls of the form
new("MLSeq", ...). This type
of objects is created as a result of
classify function of
It is then used in
predictClassify function for predicting the class labels of new samples.
stores the data in
stores all the information about classification model. The object is from subclass
MLSeqModelInfo-class for details.
metadata for MLSeq object. The object is from subclass
MLSeqMetaData-class for details.
MLSeq class stores the results of
classify function and offers further slots that are populated
during the analysis. The slot
inputObject stores the raw and transformed data throughout the classification. The slot
modelInfo stores all the information about classification model. These results may contain the classification table
and performance measures such as accuracy rate, sensitivity, specifity, positive and negative predictive values, etc. It also
contains information on classification method, normalization and transformation used in the classification model.
Lastly, the slot
metaData stores the information about modified or updated slots in MLSeq object.
Gokmen Zararsiz, Dincer Goksuluk, Selcuk Korkmaz, Vahap Eldem, Bernd Klaus, Ahmet Ozturk and Ahmet Ergun Karaagaoglu
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