Changed module name so it follows common convention.
Added test for classifier.error.
Code for profiling classifier.error.
Vectorized classifier.error; achieved speedup ~100%.
Changed function name so it follows common code convention.
Added a test for classifier.update_table
Profiling function for classifier.update_table
Removing extraneous 'pass' statement.
Vectorized classifier.update_table. Now code runs ~35x faster.
Assorted edits to make source code more pep8 compliant.
Added internal function classifier._apply_transform that calculates the classification error and the updated decision table.
Added function to hash input table. Corrected ordering of parameters in call to 'assert'-like methods in tests.
classifier.py
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* Renamed function update_table as update_weights.
* In the same function, now the weights are normalized again at the end of the function.
* Added a function (apply_feature_selection) that is given the indices of selected features and performs the dimension reduction; then, the function calculates the classification error for this iteration and builds the new decision error.
* TODO: think of better name for the function described above.
* Deleted functions that were no longer used in the current pipeline.
* Deleted hardcoded paths.
* Deleted a lot of commented out code.

test/test_classifier.py
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Minor adjustments to changes described above.

test/profiling.py
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Minor adjustments to changes described above.
Docstring for function.
Edited doc comment; removed superfluos line in profiling.py
Removed unused functions.
Merge pull request #1 from santoscarlos/master

Vectorizing code