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Change Log 0.1.10
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- - Added ( aggregative) bootstrap for deriving confidence regions (confidence intervals, ellipses in the simplex, or
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+ - Added aggregative bootstrap for deriving confidence regions (confidence intervals, ellipses in the simplex, or
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ellipses in the CLR space). This method is efficient as it leverages the two-phases of the aggregative quantifiers.
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This method applies resampling only to the aggregation phase, thus avoiding to train many quantifiers, or
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classify multiple times the instances of a sample. See the new example no. 15.
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- import method . confidence
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+ from . import confidence
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from . import base
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from . import aggregative
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from . import non_aggregative
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aggregative .KDEyML ,
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aggregative .KDEyCS ,
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aggregative .KDEyHD ,
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- method . confidence .BayesianCC
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+ confidence .BayesianCC
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}
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BINARY_METHODS = {
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aggregative .KDEyML ,
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aggregative .KDEyCS ,
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aggregative .KDEyHD ,
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- method . confidence .BayesianCC
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+ confidence .BayesianCC
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}
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NON_AGGREGATIVE_METHODS = {
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