Metadata-Version: 2.1
Name: LGBtrainer
Version: 0.1
Summary: Find LGBM Hyperparams and train the model
Home-page: https://github.com/Rajshinde07/LGBtrainer
Author: Rajwardhan Shinde
Author-email: rajshinde55553@gmail.com
License: UNKNOWN
Description: # LGBtrainer helps you find hyper params for LGBM and simplifies the process of training the model and finding hyperparams.
        
        * Parameters:-
        
        1. train = it should be your train dataset(which is fit for training purpose)
        2. test = it should be your test dataset(which is fit for testing purpose)
        3. y_train = it should be your target column or values(same rows as train)
        4. cv = the number of splits or folds(it is used for both finding hyperparams + training the model)
        5. num_rounds = number of training rounds(it is used for both finding hyperparams + training the model)
        6. metric = only 'auc' and 'rmse' can be used(For now only these two are supported)
        7. objective = 'binary' or 'regression' or any other can be provided
        8. max_eval = number of evaluations performed for finding params(note:- larger number might take more time depending on size of dataset)
        
        * Example:-
        
        ```
        -from LGBtrainer import Model
        -model = Model(train, test, y_train, metric='auc', objective='binary', max_eval=3, cv=5)
        -params = model.get_params()
        -predictions = model.lgb_model(params)
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
