MaStockMLMachine

class zvt.ml.ml.MaStockMLMachine(entity_ids: Optional[List[str]] = None, start_timestamp: Union[str, pandas._libs.tslibs.timestamps.Timestamp] = '2015-01-01', end_timestamp: Union[str, pandas._libs.tslibs.timestamps.Timestamp] = '2021-12-01', predict_start_timestamp: Union[str, pandas._libs.tslibs.timestamps.Timestamp] = '2021-06-01', predict_steps: int = 20, level: Union[zvt.contract.IntervalLevel, str] = IntervalLevel.LEVEL_1DAY, adjust_type: Optional[Union[zvt.contract.AdjustType, str]] = None, data_provider: Optional[str] = None, label_method: str = 'raw')

Bases: zvt.ml.ml.StockMLMachine

__init__(entity_ids: Optional[List[str]] = None, start_timestamp: Union[str, pandas._libs.tslibs.timestamps.Timestamp] = '2015-01-01', end_timestamp: Union[str, pandas._libs.tslibs.timestamps.Timestamp] = '2021-12-01', predict_start_timestamp: Union[str, pandas._libs.tslibs.timestamps.Timestamp] = '2021-06-01', predict_steps: int = 20, level: Union[zvt.contract.IntervalLevel, str] = IntervalLevel.LEVEL_1DAY, adjust_type: Optional[Union[zvt.contract.AdjustType, str]] = None, data_provider: Optional[str] = None, label_method: str = 'raw') → None

Parameters

• entity_ids –

• start_timestamp –

• end_timestamp –

• predict_start_timestamp –

• predict_steps –

• level –

• adjust_type –

• data_provider –

• label_method – raw, change, or behavior_cls

build_feature(entity_ids: List[str], start_timestamp: pandas._libs.tslibs.timestamps.Timestamp, end_timestamp: pandas._libs.tslibs.timestamps.Timestamp) → pandas.core.frame.DataFrame

Parameters

• entity_ids –

• start_timestamp –

• end_timestamp –

Returns

entity_schema

alias of zvt.domain.meta.stock_meta.Stock