automl.time_series.ts_data
TimeSeriesDataset Objects
@dataclass
class TimeSeriesDataset()
to_univariate
def to_univariate() -> Dict[str, "TimeSeriesDataset"]
Convert a multivariate TrainingData to a dict of univariate ones @param df: @return:
fourier_series
def fourier_series(feature: pd.Series, name: str)
Assume feature goes from 0 to 1 cyclically, transform that into Fourier @param feature: input feature @return: sin(2pifeature), cos(2pifeature)
DataTransformerTS Objects
class DataTransformerTS()
Transform input time series training data.
fit
def fit(X: Union[DataFrame, np.array], y)
Fit transformer.
Arguments:
X- A numpy array or a pandas dataframe of training data.y- A numpy array or a pandas series of labels.
Returns:
X- Processed numpy array or pandas dataframe of training data.y- Processed numpy array or pandas series of labels.