Implements Alex J.Smola and Bernhard Scholkopf sequential minimal optimization
algorithm for training a support vector regression using polynomial
or RBF kernels.
SMOreg() -
Constructor for class weka.classifiers.functions.SMOreg
SMOset - class weka.classifiers.functions.supportVector.SMOset.
Stores a set of integer of a given size.
SMOset(int) -
Constructor for class weka.classifiers.functions.supportVector.SMOset
Helper function for cutting back m_regressions to the set of classifiers (corresponsing to the number of
LogitBoost iterations) that gave the smallest error.
This function gets called when the user has clicked something
It will amend the current selection or connect the current selection
to the new selection.
This function sets what the m_numeric flag to represent the passed class
it also performs the normalization of the attributes if applicable
and sets up the info to normalize the class.
The given String is supposed to have no whitespace-signs
and to collect classes as a comma-separated list delimited by
left- and right-brackets - so superclasses are collected as
comma-separated list of substrings delimited by left- and
right-brackets.
Sets whether if the word frequencies in a document should be transformed
into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
Set the number of all conditions that could appear
in a rule in this RuleStats object, if the number set
is smaller than 0 (typically -1), then it calcualtes
based on the data store
Parses a given list of options
Valid options are:
-X
Specify constant rate at which attributes are eliminated per invocation
of the support vector machine.
Sorts a given array of integers in ascending order and returns an
array of integers with the positions of the elements of the original
array in the sorted array.
Sorts a given array of doubles in ascending order and returns an
array of integers with the positions of the elements of the
original array in the sorted array.
Sorts a given array of doubles in ascending order and returns an
array of integers with the positions of the elements of the original
array in the sorted array.
Stratifies a set of instances according to its class values
if the class attribute is nominal (so that afterwards a
stratified cross-validation can be performed).