Predicting | R Documentation |
This class is designed for predictions.
The Predicting is structured as followed:
PredictLayer: Exists for each modality.
PredictData: Related class for modality-specific predictions.
PredictMetaLayer: Related class for meta predictions.
PredictData: Specific to the meta layer, it is set up internally after cross-validation.
Use the function train
for training and predict
for predicting.
TODO: Do not export me.
fuseMLR::HashTable
-> Predicting
new()
constructor
Predicting$new(id, ind_col)
id
character
Predicting id.
ind_col
character
Name of column of individuals IDS
print()
Printer
Predicting$print(...)
...
any
createMetaTestData()
Creates a new modality-specific predictions dataset based on layer predictions.
Predicting$createMetaTestData(meta_layer_id)
meta_layer_id
(character(1)
)
ID of the meta layer where the testing meta data will be stored.
A TestData is returned.
getIndIDs()
Gather individual IDs from all layer.
Predicting$getIndIDs()
A data.frame
containing individuals IDs.
getPredictMetaLayer()
Getter of the meta layer.
Predicting$getPredictMetaLayer()
Object from class PredictMetaLayer
getIndCol()
Getter of the individual column name.
Predicting$getIndCol()
TrainLayer
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