Python lightgbm.__version__() Examples

The following are 2 code examples of lightgbm.__version__(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module lightgbm , or try the search function .
Example #1
Source File: lightgbm.py    From mljar-supervised with MIT License 5 votes vote down vote up 
def __init__(self, params):
        super(LightgbmAlgorithm, self).__init__(params)
        self.library_version = lgb.__version__

        self.explain_level = params.get("explain_level", 0)
        self.rounds = additional.get("max_rounds", 10000)
        self.max_iters = 1
        self.early_stopping_rounds = additional.get("early_stopping_rounds", 50)

        self.learner_params = {
            "boosting_type": "gbdt",
            "objective": self.params.get("objective", "binary"),
            "metric": self.params.get("metric", "binary_logloss"),
            "num_threads": multiprocessing.cpu_count(),
            "num_leaves": self.params.get("num_leaves", 31),
            "learning_rate": self.params.get("learning_rate", 0.1),
            "feature_fraction": self.params.get("feature_fraction", 1.0),
            "bagging_fraction": self.params.get("bagging_fraction", 1.0),
            "min_data_in_leaf": self.params.get("min_data_in_leaf", 20),
            "verbose": -1,
            "seed": self.params.get("seed", 1),
        }
        if "num_class" in self.params:  # multiclass classification
            self.learner_params["num_class"] = self.params.get("num_class")

        logger.debug("LightgbmLearner __init__")
Example #2
Source File: lightgbm.py    From mlflow with Apache License 2.0 5 votes vote down vote up 
def get_default_conda_env():
    """
    :return: The default Conda environment for MLflow Models produced by calls to
             :func:`save_model()` and :func:`log_model()`.
    """
    import lightgbm as lgb

    return _mlflow_conda_env(
        additional_conda_deps=None,
        # LightGBM is not yet available via the default conda channels, so we install it via pip
        additional_pip_deps=[
            "lightgbm=={}".format(lgb.__version__),
        ],
        additional_conda_channels=None)