lares (version 5.2.13)

h2o_predict_MOJO: Calculate predictions of h2o Models

Description

h2o_predict_MOJO lets the user predict using the h2o .zip file containing the MOJO files. Note that it works with the files generated when using the function export_results()

h2o_predict_binary lets the user predict using the h2o binary file. Note that it works with the files generated when using the function export_results(). Recommendation: use the h2o_predict_MOJO() function when possible - it let's you change h2o's version without problem.

h2o_predict_model lets the user get scores from a H2O Model Object.

h2o_predict_API lets the user get the score from an API service

Usage

h2o_predict_MOJO(df, model_path, method = "mojo", batch = 300)
h2o_predict_binary(df, model_path, sample = NA)
h2o_predict_model(df, model)
h2o_predict_API(df, api, exclude = "tag")

Value

data.frame with predicted results.

vector with predicted results.

data.frame with predicted results.

vector with predicted results.

Arguments

df

Dataframe/Vector. Data to insert into the model.

model_path

Character. Relative model path directory or zip file.

method

Character. One of "mojo" or "json".

batch

Integer. Run n batches at a time for "json" method.

sample

Integer. How many rows should the function predict?

model

h2o model Object

api

Character. API URL.

exclude

Character. Name of the variables to exclude.

See Also

Other Machine Learning: ROC(), conf_mat(), export_results(), gain_lift(), h2o_automl(), h2o_selectmodel(), impute(), iter_seeds(), lasso_vars(), model_metrics(), model_preprocess(), msplit()