kappaml_core package

Subpackages

• kappaml_core.datasets package
  • Submodules
  • kappaml_core.datasets.movielens25M module
  • Module contents
• kappaml_core.meta package
  • Submodules
  • kappaml_core.meta.base module
    • MetaEstimator
      • MetaEstimator.best_model
      • MetaEstimator.learn_one()
      • MetaEstimator.predict_one()
  • kappaml_core.meta.meta_classifier module
    • MetaClassifier
  • kappaml_core.meta.meta_regressor module
    • MetaRegressor
  • Module contents
    • MetaClassifier
    • MetaRegressor

Submodules

kappaml_core.cli module

This is a skeleton file that can serve as a starting point for a Python console script.

kappaml_core.cli.demo(demo_name)

Demo all the KappaML models

kappaml_core.cli.evaluate(model)

kappaml_core.cli.evaluate_classifier(model)

kappaml_core.cli.fib(n)

Fibonacci example function

Parameters:

n (int) – integer

Returns:

n-th Fibonacci number

Return type:

int

kappaml_core.cli.main(args)

Wrapper allowing fib() and demo() to be called with string arguments in a CLI fashion

Parameters:

args (List[str]) – command line parameters as list of strings (for example ["--verbose", "42"]).

kappaml_core.cli.parse_args(args)

Parse command line parameters

Parameters:

args (List[str]) – command line parameters as list of strings (for example ["--help"]).

Returns:

command line parameters namespace

Return type:

argparse.Namespace

kappaml_core.cli.run()

Calls main() passing the CLI arguments extracted from sys.argv

This function can be used as entry point to create console scripts with setuptools.

kappaml_core.cli.setup_logging(loglevel)

Setup basic logging

Parameters:

loglevel (int) – minimum loglevel for emitting messages

Module contents