api reference

Author: mathias-von-ottenbreit

API_REFERENCE.md

@@ -14,10 +14,10 @@ The learning rate. Must be greater than zero and not more than one. The higher t
 Used to randomly split training observations into training and validation if ***validation_set_indexes*** is not specified when fitting.
 
 #### family (default = "gaussian")
-Determines the loss function used. Allowed values are "gaussian", "binomial", "poisson", "gamma" and "tweedie". This is used together with ***link_function***. This is not intended to be a tuning parameter because it defines how the loss function is calculated. However, if you wish to tune it then the method ***get_validation_group_mse()*** provides a useful tuning metric.
+Determines the loss function used. Allowed values are "gaussian", "binomial", "poisson", "gamma" and "tweedie". This is used together with ***link_function***. ***family*** is not intended to be a tuning parameter because it defines how the loss function is calculated. However, if you wish to tune it then the method ***get_validation_group_mse()*** provides a useful tuning metric.
 
 #### link_function (default = "identity")
-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 values other than "identity" typically require a significantly higher ***m*** (or ***v***) in order to converge. This is not intended to be a tuning parameter because it defines the model structure. However, if you wish to tune it then the method ***get_validation_group_mse()*** provides a useful tuning metric.
+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 values other than "identity" typically require a significantly higher ***m*** (or ***v***) in order to converge. ***link_function*** is not intended to be a tuning parameter because it defines the model structure. However, if you wish to tune it then the method ***get_validation_group_mse()*** provides a useful tuning metric.
 
 #### n_jobs (default = 0)
 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).