Added one hot encoding to transformers #243
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| The name of the source that will be transformed. | ||
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| """ | ||
| def __init__(self, data_stream, num_classes, source_name='targets', |
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You don't need an additional source_name kwarg, as which_sources will already filter out the sources to be transformed.
In fact, I think having a targets default value might not be worth it as well.
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@markusnagel sorry about the delay, and thanks a lot for your contribution! |
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Thanks for your feedback. Indeed the source_name was completely unnecessary. I implemented your suggestions, what do you think of it? |
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@vdumoulin , I squashed the corrections into one commit. Any idea what's going on with travis? |
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No idea. I restarted the build yesterday and had the same error, I'm trying again today. |
…ests for input validation.
Conflicts: tests/transformers/test_transformers.py
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We added a OneHotEncoding class that transforms a given source (in int) to one-hot-encoding (also known as 1-of-K encoding) as well as a corresponding test.
One-hot-encoding is useful if (1) a problem has many classes and thus by storing the class number space can be saved and (2) if a problem can be treated as different types of problems (e.g. ordinal regression, classification).