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Last data update: 2014.03.03

R: Manipulate training and testsets 'ZITrain'/'ZITest' objects

ZITrain

R Documentation

Manipulate training and testsets 'ZITrain'/'ZITest' objects

Description

'ZITrain' contain a hierarchy of classes (taxonomic or not) and a link to a series of items belonging to these classes. It can be obtained after manual or automatic classification of various objects from .zid or .zidb files. 'ZITest' objects are almost identical, but with a constraint on the classes that must match the ones of the reference 'ZItrain' or 'ZIClass' object (a necessity to allow for comparisons)!

Usage

prepareTrain(traindir, zidbfiles, template = c("[Basic]", "[Detailed]",
    "[Very detailed]"), classes = NULL, ...)
addToTrain(traindir, zidbfiles, classes = NULL, ...)
getTrain(traindir, creator = NULL, desc = NULL, keep_ = FALSE, na.rm = FALSE)

prepareTest(testdir, zidbfiles, template, classes = NULL, ...)
addToTest(testdir, zidbfiles, classes = NULL, ...)
getTest(testdir, creator = NULL, desc = NULL, keep_ = NA, na.rm = FALSE)

template(object, ...)
## Default S3 method:
template(object, ...)

recode(object, ...)
## S3 method for class 'ZITrain'
recode(object, new.levels, depth, ...)
## S3 method for class 'ZITest'
recode(object, new.levels, depth, ...)

Arguments

`traindir`	the root directory of the training set.
`testdir`	the root directory of the test set.
`zidbfiles`	.zidb files or .zid files to use for data and vignettes in the training set.
`template`	file containing subdirectories template to use for creating classes in the training or test set. Either a defaut template between [], or the name of a .zic file, or a template extracted from a 'ZITrain' or 'ZIClass' object using `template(object)` (with the `add.others` argument to TRUE for `prepareTest()` and to `FALSE` for `prepareTrain()`)
`classes`	if vignettes are already classified in the zid(b) files, should they be sorted that way in the created training or test set? If not `NULL`, indicate the name of the classification column (usually, `Class` for manual classification or `Predicted` for automatic predictions). This can also be a 'ZIClass' or 'mlearning' object that will be used for classification of the particles first, ... or it can be a function that does the classification.
`creator`	name of the author of this classification (or the method, if done automatically).
`desc`	a short description of this manual classification.
`keep_`	do we keep items in the '_' subdirectory (corresponding to unclassified ones)? Default to `FALSE` in `getTrain()` and to `NA` for `getTest()`, which transforms all items in the '_' or one of its subdirectories into missing data.
`na.rm`	do we remove item with missing data? By default, not.
`object`	a 'ZITrain' or 'ZITest' object. For `prepareTest()`, a 'ZITrain' or 'ZIClass' object to use as reference to determine the classes to make.
`new.levels`	a character string of same length as the levels of `object$Class` with the labels of the new levels.
`depth`	the depth in the hierachy of the classes as in the `"path"` attribute of the object to use for recoding classes. If this argument is provided, `new.levels` is ignored and recomputed (and a warning is issued if both arguments are provided).
`...`	further arguments passed to the method. For `prepareXXX()` and `addToXXX()`, it is further arguments passed to the prediction function provided in `classes`, or to the `predict()` method for 'ZIClass' or 'mlearning' objects.

Author(s)

Philippe Grosjean <Philippe.Grosjean@umons.ac.be>

Examples

##TODO...