PolynomialTrendForecaster

class sktime.forecasting.trend.PolynomialTrendForecaster(regressor=None, degree=1, with_intercept=True)[source]

Forecast time series data with a polynomial trend. Default settings train a linear regression model with a 1st degree polynomial transformation of the feature.

Parameters
  • regressor (estimator object, optional (default = None)) –

    Define the regression model type. If not set, will default to

    sklearn.linear_model.LinearRegression

  • degree (int, optional (default = 1)) – Degree of polynomial function

  • with_intercept (bool, optional (default=True)) – If true, then include a feature in which all polynomial powers are zero. (i.e. a column of ones, acts as an intercept term in a linear model)

__init__(regressor=None, degree=1, with_intercept=True)[source]

Initialize self. See help(type(self)) for accurate signature.