Performs a benchmark procedure by partitioning the given data. On each of times steps size observations are removed from the data, the DD-Classifier is trained on these data and tested on the removed observations.
● Data Source:
CranContrib
● Keywords: benchmark
● Alias: ddalpha.getErrorRatePart
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Calculates the representation of the training classes in depth space.
● Data Source:
CranContrib
● Keywords: multivariate, nonparametric, robust
● Alias: depth.space.*
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Plots the functional data given in the form which is described in the topic dataf.* .
● Data Source:
CranContrib
● Keywords: functional, visualization
● Alias: plotf
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Calculates the depth of points w.r.t. a multivariate data set.
● Data Source:
CranContrib
● Keywords: multivariate, nonparametric, robust
● Alias: depth.*
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Performs a cross-validation procedure over the given data. On each step every numchunks observation is removed from the data, the DD-Classifier is trained on these data and tested on the removed observations.
● Data Source:
CranContrib
● Keywords: benchmark
● Alias: ddalpha.getErrorRateCV
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Classifies data using the DDα-classifier and a specified outsider treatment.
● Data Source:
CranContrib
● Keywords: classif, multivariate, nonparametric, robust
● Alias: ddalpha.classify
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Trains the functional DDalpha-classifier
● Data Source:
CranContrib
● Keywords: classif, functional, multivariate, nonparametric, robust
● Alias: ddalphaf.train
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Classifies data using the functional componentwise classifier.
● Data Source:
CranContrib
● Keywords: classif, functional, multivariate, nonparametric, robust
● Alias: compclassf.classify
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Calculates the representation of the training classes in depth space using spatial depth.
● Data Source:
CranContrib
● Keywords: multivariate, nonparametric, robust
● Alias: depth.space.spatial
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Builds the data depth graphs for 2-dimensional data. The graph is built using persp .
● Data Source:
CranContrib
● Keywords: visualization
● Alias: depth.graph
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