object
LogisticClassifierFromCsv
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Params(train: File, eval: File, showEval: Boolean = false, fullOutput: Boolean = false, reg: Double = 1.0, tol: Double = 1.0E-4, maxIterations: Int = 1000, opt: OptParams, help: Boolean = false) extends Product with Serializable
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This is an example app for creating a logistic classifier from data that is stored as string valued features and string valued labels, e.g.
verb=join,noun=board,prep=as,prep_obj=director,V verb=isIs,noun=chairman,prep=of,prep_obj=N.V.,N verb=named,noun=director,prep=of,prep_obj=conglomerate,N
These are examples from Ratnarparkhi's classic prepositional phrase attachment dataset, discussed in the following homework:
http://ata-s12.utcompling.com/assignments/classification
The homework includes pointers to the data and to Scala code for generating said features.
This example handles creating a feature index and getting the examples into the right data structures for training with the logistic regression classifier, which should serve as a useful example for creating features and classifiers using the API.