NEWS.md

In alex23lemm/zementisr: R client for the 'Zementis Server' API

zementisr 0.5.0

• Update hex logo format to .png and add favicons

• Add unit test for spell checking

• First CRAN submission

zementisr 0.4.2

• Modify README, vignettes and tests to align with R pmml package release 2.0.0 and Zementis Server release 10.5

zementisr 0.4.1

• Internal function get_zementis_base_url() stops adding "adapars" to base URL fetched from .Renviron

zementisr 0.4.0

Breaking changes

• apply_model() renamed to predict_pmml() which is a more intuitive function name for the common R user

• apply_model_batch() renamed to predict_pmml_batch()

Minor improvements

• predict_pmml_batch() gets two additional arguments max_threads and max_records_per_thread

zementisr 0.3.0

• get_model_metrics() gets PMML model memory and model prediction metrics from Zementis Server

• The model metrics vignette (see vignette("model-metrics")) shows how to download and visualize metrics for different kind of predictive models from Zementis Server

zementisr 0.2.0

• download_model() downloads the original PMML model source from Zementis Server

zementisr 0.1.0

• get_models() lists all models deployed to Zementis Server

• upload_model() uploads PMML model (residing in memory or saved to a file) to Zemenits Server

• get_model_properties() gets PMML model name, description, input and output field properties

• activate_model() activates PMML model on Zementis Server

• deactivate_model() deactivates PMML model on Zementis Server

• delete_model() deletes PMML model from Zementis Server

• apply_model() applies PMML model on single data record that is sent to Zementis Server

• apply_model_batch() Applies PMML model to multiple data records (a data frame in memory or a file saved to disk) that are sent to Zementis Server

• Read the Quickstart Guide vignette (see vignette("zementisr")) for an in-depth introduction to the zementisr package

alex23lemm/zementisr documentation built on Jan. 9, 2020, 1:49 a.m.