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Clone Mass | Clones in CloneSet | Parameter Count | Clone Similarity | Syntax Category [Sequence Length] |
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4 | 2 | 0 | 1.000 | stmt_list[2] |
Clone Abstraction | Parameter Bindings |
Clone Instance (Click to see clone) | Line Count | Source Line | Source File |
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1 | 4 | 225 | Bio/MaxEntropy.py |
2 | 4 | 128 | Bio/NaiveBayes.py |
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if not len(training_set): raise ValueError("No data in the training set.") if len(training_set)!=len(results): raise ValueError("training_set and results should be parallel lists.") # Rename variables for convenience. |
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if not len(training_set): raise ValueError("No data in the training set.") if len(training_set)!=len(results): raise ValueError("training_set and results should be parallel lists.") # If no typecode is specified, try to pick a reasonable one. If # training_set is a Numeric array, then use that typecode. # Otherwise, choose a reasonable default. # XXX NOT IMPLEMENTED # Check to make sure each vector in the training set has the same # dimensionality. |
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if not len(training_set): raise ValueError("No data in the training set.") if len(training_set)!=len(results): raise ValueError("training_set and results should be parallel lists.") # If no typecode is specified, try to pick a reasonable one. If # training_set is a Numeric array, then use that typecode. # Otherwise, choose a reasonable default. # XXX NOT IMPLEMENTED # Check to make sure each vector in the training set has the same # dimensionality. # Rename variables for convenience. |
CloneAbstraction |
Parameter Index | Clone Instance | Parameter Name | Value |
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None |