Rbf sampler #127
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Rbf sampler #127
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added 2 commits
April 17, 2016 16:42
Also: * refactored non_feature_columns into single instance attribute * changed n_components filtering logic to match that of the export_utils for PCA and RBF
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| # NOTE: Make sure that the class is labeled 'class' in the data file | ||
| tpot_data = pd.read_csv('PATH/TO/DATA/FILE', sep='COLUMN_SEPARATOR') | ||
| training_indices, testing_indices = train_test_split(tpot_data.index, stratify = tpot_data['class'].values, train_size=0.75, test_size=0.2$ |
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I think a ) is missing here.
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Well done! Not too bad of a code base, right? :-) I'll have to add details on how to run I'll fix the parenthesis issue now. |
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What does this PR do?
Fixes #124
Where should the reviewer start?
Check out the documentation at
documentation/pipeline_operators/kernel_approximation/RBFSampler.md.The _rbf function is in tpot.py and start at line 1092
How should this PR be tested?
By commenting out most other operators you should be able to force TPOT to make use of the RBFSampler.
Any background context you want to provide?
No
What are the relevant issues?
#124
Questions:
Yes and I have updated them.
No.