Man pages for lightgbm
Light Gradient Boosting Machine
| agaricus.test | Test part from Mushroom Data Set |
| agaricus.train | Training part from Mushroom Data Set |
| bank | Bank Marketing Data Set |
| dim | Dimensions of an 'lgb.Dataset' |
| dimnames.lgb.Dataset | Handling of column names of 'lgb.Dataset' |
| get_field | Get one attribute of a 'lgb.Dataset' |
| getinfo | Get information of an 'lgb.Dataset' object |
| lgb.convert_with_rules | Data preparator for LightGBM datasets with rules (integer) |
| lgb.cv | Main CV logic for LightGBM |
| lgb.Dataset | Construct 'lgb.Dataset' object |
| lgb.Dataset.construct | Construct Dataset explicitly |
| lgb.Dataset.create.valid | Construct validation data |
| lgb.Dataset.save | Save 'lgb.Dataset' to a binary file |
| lgb.Dataset.set.categorical | Set categorical feature of 'lgb.Dataset' |
| lgb.Dataset.set.reference | Set reference of 'lgb.Dataset' |
| lgb.dump | Dump LightGBM model to json |
| lgb.get.eval.result | Get record evaluation result from booster |
| lgb.importance | Compute feature importance in a model |
| lgb.interprete | Compute feature contribution of prediction |
| lgb.load | Load LightGBM model |
| lgb.model.dt.tree | Parse a LightGBM model json dump |
| lgb.plot.importance | Plot feature importance as a bar graph |
| lgb.plot.interpretation | Plot feature contribution as a bar graph |
| lgb.save | Save LightGBM model |
| lgb_shared_dataset_params | Shared Dataset parameter docs |
| lgb_shared_params | Shared parameter docs |
| lgb.train | Main training logic for LightGBM |
| lgb.unloader | Remove lightgbm and its objects from an environment |
| lightgbm | Train a LightGBM model |
| predict.lgb.Booster | Predict method for LightGBM model |
| readRDS.lgb.Booster | readRDS for 'lgb.Booster' models |
| saveRDS.lgb.Booster | saveRDS for 'lgb.Booster' models |
| set_field | Set one attribute of a 'lgb.Dataset' object |
| setinfo | Set information of an 'lgb.Dataset' object |
| slice | Slice a dataset |
