plotAssignments {geNetClassifier} | R Documentation |
Plots the assignment probabilities of a previous query.
plotAssignments(queryResult, realLabels, minProbAssignCoeff = 1, minDiffAssignCoeff = 0.8, totalNumberOfClasses = NULL, pointSize=0.8, identify = FALSE)
queryResult |
Object returned by |
realLabels |
Factor. Actual/real class of the samples. |
minProbAssignCoeff |
Numeric. See |
minDiffAssignCoeff |
Numeric. See |
totalNumberOfClasses |
Numeric. Total number of classes the classifier was trained with. The assignment probability is determined bassed on it. It is not needed if there are samples of all the training classes. |
pointSize |
Numeric. Point size modifier. |
identify |
Logical. If TRUE and supported (X11 or quartz devices), the plot will be interactive and clicking on a point will identify the sample the point represents. Press ESC or right-click on the plot screen to exit. |
Plot.
Main package function and classifier training: geNetClassifier
Querying the classifier: queryGeNetClassifier
########################## ## Classifier training ########################## # Load an expressionSet: library(leukemiasEset) data(leukemiasEset) # Select the train samples: trainSamples<- c(1:10, 13:22, 25:34, 37:46, 49:58) # summary(leukemiasEset$LeukemiaType[trainSamples]) # Train a classifier or load a trained one: # leukemiasClassifier <- geNetClassifier(leukemiasEset[,trainSamples], # sampleLabels="LeukemiaType", plotsName="leukemiasClassifier") data(leukemiasClassifier) # Sample trained classifier ########################## ## External Validation: ########################## # Select the samples to query the classifier # - External validation: samples not used for training testSamples <- c(1:60)[-trainSamples] # Make a query to the classifier: queryResult <- queryGeNetClassifier(leukemiasClassifier, leukemiasEset[,testSamples]) ########################## ## Plot: ########################## plotAssignments(queryResult, realLabels=leukemiasEset[,testSamples]$LeukemiaType)