зеркало из https://github.com/microsoft/LightGBM.git
fixed broken link in docs (#2623)
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@ -71,7 +71,7 @@ Core Parameters
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- ``gamma``, Gamma regression with log-link. It might be useful, e.g., for modeling insurance claims severity, or for any target that might be `gamma-distributed <https://en.wikipedia.org/wiki/Gamma_distribution#Occurrence_and_applications>`__
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- ``tweedie``, Tweedie regression with log-link. It might be useful, e.g., for modeling total loss in insurance, or for any target that might be `tweedie-distributed <https://en.wikipedia.org/wiki/Tweedie_distribution#Applications>`__
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- ``tweedie``, Tweedie regression with log-link. It might be useful, e.g., for modeling total loss in insurance, or for any target that might be `tweedie-distributed <https://en.wikipedia.org/wiki/Tweedie_distribution#Occurrence_and_applications>`__
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- ``binary``, binary `log loss <https://en.wikipedia.org/wiki/Cross_entropy>`__ classification (or logistic regression). Requires labels in {0, 1}; see ``cross-entropy`` application for general probability labels in [0, 1]
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@ -113,7 +113,7 @@ struct Config {
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// descl2 = ``quantile``, `Quantile regression <https://en.wikipedia.org/wiki/Quantile_regression>`__
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// descl2 = ``mape``, `MAPE loss <https://en.wikipedia.org/wiki/Mean_absolute_percentage_error>`__, aliases: ``mean_absolute_percentage_error``
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// descl2 = ``gamma``, Gamma regression with log-link. It might be useful, e.g., for modeling insurance claims severity, or for any target that might be `gamma-distributed <https://en.wikipedia.org/wiki/Gamma_distribution#Occurrence_and_applications>`__
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// descl2 = ``tweedie``, Tweedie regression with log-link. It might be useful, e.g., for modeling total loss in insurance, or for any target that might be `tweedie-distributed <https://en.wikipedia.org/wiki/Tweedie_distribution#Applications>`__
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// descl2 = ``tweedie``, Tweedie regression with log-link. It might be useful, e.g., for modeling total loss in insurance, or for any target that might be `tweedie-distributed <https://en.wikipedia.org/wiki/Tweedie_distribution#Occurrence_and_applications>`__
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// desc = ``binary``, binary `log loss <https://en.wikipedia.org/wiki/Cross_entropy>`__ classification (or logistic regression). Requires labels in {0, 1}; see ``cross-entropy`` application for general probability labels in [0, 1]
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// desc = multi-class classification application
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// descl2 = ``multiclass``, `softmax <https://en.wikipedia.org/wiki/Softmax_function>`__ objective function, aliases: ``softmax``
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