Package PyML :: Package containers :: Module datafunc :: Class PyVectorDataSet
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Class PyVectorDataSet

source code

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       PyVectorDataSet

A non-sparse dataset container; uses a numpy array
Instance Methods
 
__len__(self)
the number of patterns in the dataset
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getNumFeatures(self) source code
 
setNumFeatures(self, value) source code
 
fromArrayAdd(self, X) source code
 
dotProduct(self, x, y, other=None) source code
 
initializeDataMatrix(self, numPatterns, numFeatures) source code
 
addPattern(self, x, i) source code
 
getPattern(self, i) source code
 
extendX(self, other, patterns) source code
 
featureIDcompute(self) source code
 
copy(self, other, patternsToCopy, deepcopy)
deepcopy is performed by default, so the deepcopy flag is ignored
source code
 
eliminateFeatures(self, featureList)
eliminate a list of features from a dataset Input: featureList - a list of features to eliminate; these are numbers between 0 and numFeatures-1 (indices of features, not their IDs)
source code
 
getFeature(self, feature, patterns=None) source code
 
norm(self, pattern, p=1) source code
 
normalize(self, p=1)
normalize dataset according to the p-norm, p=1,2
source code
 
scale(self, w)
rescale the columns of the data matrix by a weight vector w: set X[i][j] = X[i][j] / w[j]
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translate(self, c) source code
 
mean(self, patterns=None) source code
 
std(self, patterns=None) source code
 
featureCount(self, feature, patterns=None) source code
 
featureCounts(self, patterns=None) source code
 
csvwrite(self, fileName, delim=' ', idCol=-1) source code
Class Variables
  numFeatures = property(getNumFeatures, setNumFeatures, None, '...
Class Variable Details

numFeatures

Value:
property(getNumFeatures, setNumFeatures, None, 'The number of features\
 in a dataset')