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Convert boolean features to float in training data #417

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This commit addresses a type mismatch issue in the neural network training function. The one-hot encoded rank features in the training data were boolean values, which caused a UFuncTypeError when trying to perform operations with float values in the error term formula.

To fix this, we've added a line to convert all features in the training data to float. This converts the boolean rank features to numerical values (1.0 for True, 0.0 for False), which can be used in the error term formula without causing type errors.

We've also updated the markdown documentation to explain this conversion.

This commit addresses a type mismatch issue in the neural network training function. The one-hot encoded rank features in the training data were boolean values, which caused a UFuncTypeError when trying to perform operations with float values in the error term formula.

To fix this, we've added a line to convert all features in the training data to float. This converts the boolean rank features to numerical values (1.0 for True, 0.0 for False), which can be used in the error term formula without causing type errors.

We've also updated the markdown documentation to explain this conversion.
@NotSkynet NotSkynet requested a review from a team as a code owner June 27, 2023 01:30
@NotSkynet NotSkynet requested review from SudKul and removed request for a team June 27, 2023 01:30
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I forgot to change the test_out so that it uses the new float values. Also the original seems to work fine on older python versions but not python 3.10.11 the version I used.

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