HybridSequenceClassifier-class: Sequence Detector
In SeqDetect: Sequence and Latent Process Detector

Description Details Fields Methods References

The Sequence Detector class.

Instantiates a Sequence Detector object. Constructor takes a number of parameters that define pre-processing and pre-classification stages, as well as the structure of the input consolidated data stream. These stages can be redefined again later using setInputDefinitions,HybridSequenceClassifier-method method. See the SeqDetect vignette for examples.

fields: (vector, character) - A vector of all relevant consolidated data stream fields.
timestamp_start_field: (character) - A name of the field having starting time point values.
timestamp_finish_field: (character) - A name of the field having finishing time point values.
context_field: (character) - A name of the context identifier field (key field). If NULL, then .key field is used for retrieving context identifier values.
preclassifier: (HSC_PC) - A pre-classifier object. If NULL, the Sequence Detector creates new HSC_PC_None pre-classifier, which means that the input consolidated data stream must have .clazz field for retrieving classification values (input symbols in the underlying ETTs).
preprocessor: (HSC_PP) - A pre-processing object. If NULL, the Sequence Detector creates new HSC_PP pre-processor having the same fields as define in the fields parameter, and ordering timestamp field as defined in timestamp_start_field.
decay_descriptors: (list) - A list of decay descriptors. If NULL, token decay machanism is not used. Descriptor structure can be seen in vignettes.
pattern_field: (character) - A name of the field having output symbol values, i.e., relational ETT classification output.
time_series_sequence_stats: (logical) - If TRUE, ETTs are instructed to create sequence statistics. This is used whe having input time-series data streams. If FALSE, the sequence statistics are not created.
reuse_states: (logical) - The parameter defined in [1]. ETTs are created so that each ETT have a state that represents each input symbol.
parallel_execution: (logical) - Force parallel execution of ETTs in the Sequence Detector object. Useful when we expect higher number of ETTs in the same Sequence Detector.

cleanKeys(machine_id=NULL): Sequence Detector method for removing tokens and keys
cleanKeys,HybridSequenceClassifier-method
clone(): Sequence Detector method for cloning
clone,HybridSequenceClassifier-method
compressMachines(ratio=0.5): Sequence Detector method for compressing the underlying set of ETTs
compressMachines,HybridSequenceClassifier-method
getMachineIdentifiers(): Sequence Detector method for retrieving identifiers for the underlying set of ETTs
getMachineIdentifiers,HybridSequenceClassifier-method
induceSubmachine(threshold, isolate=FALSE): Sequence Detector method for performing statistical projections on the underlying set of ETTs
induceSubmachine,HybridSequenceClassifier-method
mergeMachines(): Sequence Detector method for merging the underlying set of ETTs
mergeMachines,HybridSequenceClassifier-method
plotMachines(machine_id=NULL): Sequence Detector method for plotting the underlying set of ETTs
plotMachines,HybridSequenceClassifier-method
printMachines(machine_id=NULL, state=NULL, print_cache=TRUE, print_keys=TRUE): Sequence Detector method for printing the underlying set of ETTs to the R console
printMachines,HybridSequenceClassifier-method
process(streams, learn=TRUE, give_explain=TRUE, threshold=NULL, debug=FALSE, out_filename=NULL, ...): Sequence Detector method for processing an input streams slice
process,HybridSequenceClassifier-method
serialize(): Sequence Detector method for serializing the underlying set of ETTs definitions
serialize,HybridSequenceClassifier-method
serializeToList(): Sequence Detector method for serializing the underlying set of ETTs definitions to the list
serializeToList,HybridSequenceClassifier-method
setOutputPattern(states=c(), transitions=c(), pattern, machine_id=NULL): Sequence Detector method for setting the output alphabet to the underlying set of ETTs
setOutputPattern,HybridSequenceClassifier-method
setPreprocessor(preprocessor): Sequence Detector method for setting the pre-processor
setPreprocessor,HybridSequenceClassifier-method
setPreclassifier(preclassifier): Sequence Detector method for setting the pre-classifier
setPreclassifier,HybridSequenceClassifier-method
setInputDefinitions(fields, timestamp_start_field, timestamp_finish_field, context_field=NULL, preclassifier=NULL, preprocessor=NULL, pattern_field=NULL): Sequence Detector method for redefining the input definitions
setInputDefinitions,HybridSequenceClassifier-method

[1] D. Krleža, B. Vrdoljak, and M. Brčić, Latent Process Discovery using Evolving Tokenized Transducer, IEEE Access, vol. 7, pp. 169657 - 169676, Dec. 2019

SeqDetect documentation built on March 2, 2020, 5:08 p.m.