An aggregate of datasets. a DataAggregate object contains a list of
datasets in its datas attribute, and behaves like a dataset when it comes
to copy construction, so it can be used as a dataset object when it comes
to testing classifiers. USAGE: DataAggregate(list) - construct an object
out of a list of datasets (they do not have to be of the same kind! It is
assumed that all datasets are the same length, and have the same labels
DataAggregate(other[,optional arguments]) - copy construction - all
options supported by the dataset classes can be used.
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__init__(self,
arg,
*opt,
**args)
x.__init__(...) initializes x; see x.__class__.__doc__ for signature |
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Inherited from object :
__delattr__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__setattr__ ,
__str__
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attachKernel(self,
kernel='linear',
**args) |
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copy(self,
other,
patterns,
deepcopy)
Each class that wants to use the generic copy constructor needs to
define this function for doing class-specific copying |
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getKernelMatrix(self)
returns the kernel matrix as a numpy array |
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registerAttribute(self,
attributeName,
attributeValue=None,
action=None) |
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