GLM2 ==== Supported HTTP methods and descriptions --------------------------------------- GET GLM2 URL --- http://:/GLM2.json Input parameters ---------------- * **offset**, a Vec, expert Column to be used as an offset, if you have one.. Since version 1 * **family**, a Family, critical Family.. Since version 1 * **link**, a Link, secondary . Since version 1 * **tweedie_variance_power**, a double, secondary Tweedie variance power. Since version 1 * **prior**, a double, expert prior probability for y==1. To be used only for logistic regression iff the data has been sampled and the mean of response does not reflect reality.. Since version 1 * **disable_line_search**, a boolean, expert disable line search in all cases.. Since version 1 * **n_folds**, a int, critical validation folds. Since version 1 * **alpha**, a double[], secondary distribution of regularization between L1 and L2.. Since version 1 * **lambda**, a double[], secondary regularization strength. Since version 1 * **lambda_search**, a boolean, secondary use lambda search starting at lambda max, given lambda is then interpreted as lambda min. Since version 1 * **nlambdas**, a int, expert number of lambdas to be used in a search. Since version 1 * **lambda_min_ratio**, a double, expert min lambda used in lambda search, specified as a ratio of lambda_max. Since version 1 * **max_predictors**, a int, expert lambda_search stop condition: stop training when model has more than than this number of predictors (or don't use this option if -1).. Since version 1 * **strong_rules**, a boolean, secondary use strong rules to filter out inactive columns. Since version 1 * **standardize**, a boolean, critical Standardize numeric columns to have zero mean and unit variance.. Since version 1 * **intercept**, a boolean, critical Include intercept term in the model.. Since version 1 * **non_negative**, a boolean, critical Restrict coefficients to be non-negative.. Since version 1 * **beta_constraints**, a Frame, expert lower bounds for coefficients. Since version 1 * **use_all_factor_levels**, a boolean, secondary By default, first factor level is skipped from the possible set of predictors. Set this flag if you want use all of the levels. Needs sufficient regularization to solve!. Since version 1 * **variable_importances**, a boolean, secondary Compute variable importances for input features. NOTE: If use_all_factor_levels is off the importance of the base level will NOT be shown.. Since version 1 * **beta_epsilon**, a double, secondary beta_eps. Since version 1 * **max_iter**, a int, critical max-iterations. Since version 1 * **higher_accuracy**, a boolean, secondary use line search (slower speed, to be used if glm does not converge otherwise). Since version 1 Output JSON elements -------------------- * **_wgiven**, a double[] . Since version 1, secondary * **_proximalPenalty**, a double . Since version 1, secondary * **_beta**, a double[] . Since version 1, secondary * **_runAllLambdas**, a boolean . Since version 1, secondary * **tweedie_link_power**, a double Tweedie link power. Since version 1, secondary * **lambda_max**, a double lambda_value max. Since version 1, secondary HTTP response codes ------------------- 200 OK Success and error responses are identical.