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object --+ | MLDataSet --+ | MLQuantDataSet
a data set for holding quantized data **Note** this is intended to be a read-only data structure (i.e. after calling the constructor you cannot touch it) **Big differences to MLDataSet** 1) data are stored in a numpy array since they are homogenous 2) results are assumed to be quantized (i.e. no qBounds entry is required)
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calculates the number of possible values of each variable **Arguments** -data: a list of examples to be used **Returns** a list of nPossible values for each variable
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returns a list of named examples **Note** a named example is the result of prepending the example name to the data list
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returns a *copy* of the data
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returns the input data **Note** _inputData_ means the examples without their result fields (the last _NResults_ entries)
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Returns the result fields from each example
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Constructor **Arguments** - data: a list of lists containing the data. The data are copied, so don't worry about us overwriting them. - nVars: the number of variables - nPts: the number of points - nPossibleVals: an list containing the number of possible values for each variable (should contain 0 when not relevant) This is _nVars_ long - qBounds: a list of lists containing quantization bounds for variables which are to be quantized (note, this class does not quantize the variables itself, it merely stores quantization bounds. an empty sublist indicates no quantization for a given variable This is _nVars_ long - varNames: a list of the names of the variables. This is _nVars_ long - ptNames: the names (labels) of the individual data points This is _nPts_ long - nResults: the number of results columns in the data lists. This is usually 1, but can be higher.
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