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API_REFERENCE.md

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Determines the loss function used. Allowed values are "gaussian", "binomial", "poisson", "gamma" and "tweedie". This is used together with ***link_function***. Please note that the implementation of values other than "gaussian" is experimental.
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#### link_function (default = "identity")
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Determines how the linear predictor is transformed to predictions. Allowed values are "identity", "logit" and "log". For logistic regression use ***family***="binomial" and ***link_function***="logit". For a multiplicative model use the "log" ***link_function*** and a ***family*** that is not "binomial". The ***family*** "poisson", "gamma" or "tweedie" should only be used with the "log" ***link_function***. Invalid combinations of ***family*** and ***link_function*** may result in a warning message when fitting the model and/or a poor model fit. Please note that the implementation of values other than "identity" is experimental.
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Determines how the linear predictor is transformed to predictions. Allowed values are "identity", "logit" and "log". For an ordinary regression model use ***family*** "gaussian" and ***link_function*** "identity". For logistic regression use ***family*** "binomial" and ***link_function*** "logit". For a multiplicative model use the "log" ***link_function***. The "log" ***link_function*** often works best with a "poisson", "gamma" or "tweedie" ***family***, depending on the data. The ***family*** "poisson", "gamma" or "tweedie" should only be used with the "log" ***link_function***. Inappropriate combinations of ***family*** and ***link_function*** may result in a warning message when fitting the model and/or a poor model fit. Please note that the implementation of values other than "identity" is experimental.
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#### n_jobs (default = 0)
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Multi-threading parameter. If ***0*** then uses all available cores for multi-threading. Any other positive integer specifies the number of cores to use (***1*** means single-threading).

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