Python Client API for machine learning algorithms
Contents:
- Python Machine Learning Client for SAP HANA
- Installation Guide
- hana-ml Tutorials
- Changelog
- hana_ml.dataframe
quotename()
ConnectionContext
ConnectionContext.enable_abap_sql()
ConnectionContext.disable_abap_sql()
ConnectionContext.close()
ConnectionContext.add_primary_key()
ConnectionContext.copy()
ConnectionContext.create_schema()
ConnectionContext.create_table()
ConnectionContext.create_virtual_table()
ConnectionContext.drop_procedure()
ConnectionContext.drop_view()
ConnectionContext.drop_table()
ConnectionContext.copy_to_data_lake()
ConnectionContext.explain_plan_statement()
ConnectionContext.has_schema()
ConnectionContext.has_table()
ConnectionContext.hana_version()
ConnectionContext.get_current_schema()
ConnectionContext.get_tables()
ConnectionContext.get_procedures()
ConnectionContext.get_temporary_tables()
ConnectionContext.get_connection_id()
ConnectionContext.cancel_session_process()
ConnectionContext.restart_session()
ConnectionContext.clean_up_temporary_tables()
ConnectionContext.hana_major_version()
ConnectionContext.is_cloud_version()
ConnectionContext.sql()
ConnectionContext.execute_sql()
ConnectionContext.table()
ConnectionContext.upsert_streams_data()
ConnectionContext.update_streams_data()
ConnectionContext.to_sqlalchemy()
DataFrame
DataFrame.columns
DataFrame.shape
DataFrame.name
DataFrame.quoted_name
DataFrame.description
DataFrame.description_ext
DataFrame.declare_lttab_usage()
DataFrame.disable_validate_columns()
DataFrame.enable_validate_columns()
DataFrame.add_id()
DataFrame.add_constant()
DataFrame.alias()
DataFrame.count()
DataFrame.diff()
DataFrame.drop()
DataFrame.distinct()
DataFrame.drop_duplicates()
DataFrame.dropna()
DataFrame.deselect()
DataFrame.has_constant_columns()
DataFrame.drop_constant_columns()
DataFrame.dtypes()
DataFrame.empty()
DataFrame.filter()
DataFrame.has()
DataFrame.head()
DataFrame.hasna()
DataFrame.fillna()
DataFrame.get_table_structure()
DataFrame.join()
DataFrame.set_name()
DataFrame.set_index()
DataFrame.save()
DataFrame.save_nativedisktable()
DataFrame.split_column()
DataFrame.concat_columns()
DataFrame.nullif()
DataFrame.replace()
DataFrame.sort()
DataFrame.sort_values()
DataFrame.sort_index()
DataFrame.select()
DataFrame.set_operations()
DataFrame.union()
DataFrame.collect()
DataFrame.geometries
DataFrame.srids
DataFrame.rename_columns()
DataFrame.auto_cast()
DataFrame.cast()
DataFrame.tail()
DataFrame.to_head()
DataFrame.to_tail()
DataFrame.summary()
DataFrame.stats
DataFrame.describe()
DataFrame.bin()
DataFrame.agg()
DataFrame.is_numeric()
DataFrame.corr()
DataFrame.min()
DataFrame.max()
DataFrame.sum()
DataFrame.median()
DataFrame.mean()
DataFrame.stddev()
DataFrame.value_counts()
DataFrame.pivot_table()
DataFrame.generate_table_type()
DataFrame.rearrange()
DataFrame.set_source_table()
DataFrame.to_pickle()
DataFrame.to_datetime()
DataFrame.generate_feature()
DataFrame.mutate()
read_pickle()
create_dataframe_from_pandas()
create_dataframe_from_spark()
melt()
create_dataframe_from_shapefile()
import_csv_from()
- hana_ml.algorithms.apl package
- hana_ml.algorithms.pal package
- Algorithms
- Topics
- Model Evaluation and Parameter Selection
- Successive Halving and Hyperband for Parameter Selection
- Biased Linear Models
- Model State for Real-Time Scoring
- Local Interpretability of Models
- Explaining the Forecasts of ARIMA
- Methods for Residual Extraction in Time-Series Outlier Detection
- Methods of Outlier Detection from Residual
- Genetic Optimization in AutoML
- Probability Density Functions for MCMC Sampling
- Miscellaneous Topics
- Precomputed Distance Matrix as input data in UnifiedClustering
- Parameters for Missing Value Handling in HANA DataFrame
- Permutation Feature Importance
- Permutation Feature Importance for Time Series
- Parameter Mappings
- hana_ml.visualizers package
- hana_ml.visualizers.eda
- hana_ml.visualizers.metrics
- hana_ml.visualizers.m4_sampling
- hana_ml.visualizers.model_debriefing
- hana_ml.visualizers.dataset_report
- hana_ml.visualizers.shap
- hana_ml.visualizers.unified_report
- hana_ml.visualizers.visualizer_base
- hana_ml.visualizers.digraph
- hana_ml.visualizers.word_cloud
- hana_ml.visualizers.automl_progress
- hana_ml.visualizers.automl_report
- hana_ml.visualizers.time_series_report
- hana_ml.visualizers.automl_config
- hana_ml.ml_exceptions
- hana_ml.model_storage
ModelStorageError
ModelStorage
ModelStorage.export_model()
ModelStorage.load_model_from_files()
ModelStorage.import_model()
ModelStorage.list_models()
ModelStorage.model_already_exists()
ModelStorage.change_storage_type()
ModelStorage.save_model()
ModelStorage.save_model_to_files()
ModelStorage.delete_model()
ModelStorage.delete_models()
ModelStorage.load_mlflow_model()
ModelStorage.clean_up()
ModelStorage.load_model()
ModelStorage.get_model_card()
ModelStorage.display_model_report()
ModelStorage.enable_persistent_memory()
ModelStorage.disable_persistent_memory()
ModelStorage.load_into_memory()
ModelStorage.unload_from_memory()
ModelStorage.set_data_lake_container()
ModelStorage.set_schedule()
ModelStorage.display_hana_schedule()
ModelStorage.start_schedule()
ModelStorage.terminate_schedule()
ModelStorage.set_logfile()
ModelStorage.upgrade_meta()
- hana_ml.artifacts package
- hana_ml.docstore package
- hana_ml.spatial package
- hana_ml.graph package
- hana_ml.graph.algorithms package
ShortestPath
Neighbors
NeighborsSubgraph
KShortestPaths
TopologicalSort
ShortestPathsOneToAll
StronglyConnectedComponents
WeaklyConnectedComponents
AlgorithmBase
AlgorithmBase.signature_from_cols()
AlgorithmBase.projection_expr_from_cols()
AlgorithmBase._default_vertex_cols()
AlgorithmBase._default_edge_cols()
AlgorithmBase._default_vertex_select()
AlgorithmBase._default_edge_select()
AlgorithmBase._process_parameters()
AlgorithmBase._validate_parameters()
AlgorithmBase.execute()
- hana_ml.text.tm package
- hana_ml.hana_scheduler
HANAScheduler
HANAScheduler.check_scheduler_job_exist()
HANAScheduler.list_schedules()
HANAScheduler.get_job_names()
HANAScheduler.display_schedule_status()
HANAScheduler.set_schedule()
HANAScheduler.delete_schedule()
HANAScheduler.delete_schedules()
HANAScheduler.clean_up_schedules()
HANAScheduler.create_training_schedule()
HANAScheduler.create_applying_schedule()
HANAScheduler.create_scoring_schedule()
- FAQs