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For resampled learners, the predictions from different iterations are combined into one. That is, for example for cross-validation, the predictions appear on a single line even though they were made by different models. There is currently no facility to separate the predictions for different resampling iterations.
plotViperCharts(obj, chart = "rocc", browse = TRUE, auth.key = NULL, task.id = NULL)Prediction | (list of) ResampleResult | BenchmarkResult]
Single prediction object, list of them, single resample result, list of them, or a benchmark result.
In case of a list probably produced by different learners you want to compare, then
name the list with the names you want to see in the plots, probably
learner shortnames or ids.character(1)]
First chart to display in focus in browser.
All other charts can be displayed by clicking on the browser page menu.
Default is “rocc”.logical(1)]
Open ViperCharts plot in web browser? If not you simple get the URL returned.
Calls browseURL.
Default is TRUE.character(1)]
API key to use for call to Viper charts website.
Only required if you want the chart to be private.
Default is NULL.character(1)]
Selected task in BenchmarkResult to do plots for, ignored otherwise.
Default is first task.character(1)]. Invisibly returns the ViperCharts URL.
asROCRPrediction,
getPredictionProbabilities,
getPredictionResponse,
predict.WrappedModel,
setPredictThreshold,
setPredictTypeOther roc: asROCRPrediction
## Not run:
# lrn1 = makeLearner("classif.logreg", predict.type = "prob")
# lrn2 = makeLearner("classif.rpart", predict.type = "prob")
# b = benchmark(list(lrn1, lrn2), pid.task)
# z = plotViperCharts(b, chart = "lift", browse = TRUE)
# ## End(Not run)
Run the code above in your browser using DataLab