GLM2

Supported HTTP methods and descriptions

GET GLM2

URL

http://<h2oHost>:<h2oApiPort>/GLM2.json

Input parameters

  • offset, a Vec, <i>expert</i>

    Column to be used as an offset, if you have one.. Since version 1

  • family, a Family, <i>critical</i>

    Family.. Since version 1

  • link, a Link, <i>secondary</i>

    . Since version 1

  • tweedie_variance_power, a double, <i>secondary</i>

    Tweedie variance power. Since version 1

  • prior, a double, <i>expert</i>

    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, <i>expert</i>

    disable line search in all cases.. Since version 1

  • n_folds, a int, <i>critical</i>

    validation folds. Since version 1

  • alpha, a double[], <i>secondary</i>

    distribution of regularization between L1 and L2.. Since version 1

  • lambda, a double[], <i>secondary</i>

    regularization strength. Since version 1

  • lambda_search, a boolean, <i>secondary</i>

    use lambda search starting at lambda max, given lambda is then interpreted as lambda min. Since version 1

  • nlambdas, a int, <i>expert</i>

    number of lambdas to be used in a search. Since version 1

  • lambda_min_ratio, a double, <i>expert</i>

    min lambda used in lambda search, specified as a ratio of lambda_max. Since version 1

  • max_predictors, a int, <i>expert</i>

    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, <i>secondary</i>

    use strong rules to filter out inactive columns. Since version 1

  • standardize, a boolean, <i>critical</i>

    Standardize numeric columns to have zero mean and unit variance.. Since version 1

  • intercept, a boolean, <i>critical</i>

    Include intercept term in the model.. Since version 1

  • non_negative, a boolean, <i>critical</i>

    Restrict coefficients to be non-negative.. Since version 1

  • beta_constraints, a Frame, <i>expert</i>

    lower bounds for coefficients. Since version 1

  • use_all_factor_levels, a boolean, <i>secondary</i>

    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, <i>secondary</i>

    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, <i>secondary</i>

    beta_eps. Since version 1

  • max_iter, a int, <i>critical</i>

    max-iterations. Since version 1

  • higher_accuracy, a boolean, <i>secondary</i>

    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.