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Regression

distribution/lib/Standard/Base/0.0.0-dev/docs/api/Data/Regression.md

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Enso Signatures 1.0

module Standard.Base.Data.Regression

  • type Fit_Error
    • Error message:Standard.Base.Any.Any
    • handle_java_exception -> Standard.Base.Any.Any
    • to_display_text self -> Standard.Base.Any.Any
  • type Fitted_Model
    • Exponential a:Standard.Base.Data.Numbers.Number b:Standard.Base.Data.Numbers.Number r_squared:Standard.Base.Data.Numbers.Number=
    • Linear slope:Standard.Base.Data.Numbers.Number intercept:Standard.Base.Data.Numbers.Number r_squared:Standard.Base.Data.Numbers.Number=
    • Logarithmic a:Standard.Base.Data.Numbers.Number b:Standard.Base.Data.Numbers.Number r_squared:Standard.Base.Data.Numbers.Number=
    • Power a:Standard.Base.Data.Numbers.Number b:Standard.Base.Data.Numbers.Number r_squared:Standard.Base.Data.Numbers.Number=
    • predict self x:Standard.Base.Any.Any -> Standard.Base.Any.Any
    • to_display_text self -> Standard.Base.Any.Any
    • to_text self -> Standard.Base.Any.Any
  • type Model
    • Exponential intercept:(Standard.Base.Data.Numbers.Number|Standard.Base.Nothing.Nothing)=
    • Linear intercept:(Standard.Base.Data.Numbers.Number|Standard.Base.Nothing.Nothing)=
    • Logarithmic
    • Power
    • fitted_model_with_r_squared constructor:Standard.Base.Any.Any a:Standard.Base.Any.Any b:Standard.Base.Any.Any known_xs:Standard.Base.Any.Any known_ys:Standard.Base.Any.Any -> Standard.Base.Any.Any
    • ln_series xs:Standard.Base.Any.Any series_name:Standard.Base.Any.Any= -> Standard.Base.Any.Any
    • to_display_text self -> Standard.Base.Any.Any
  • fit_least_squares known_xs:Standard.Base.Data.Vector.Vector known_ys:Standard.Base.Data.Vector.Vector model:Standard.Base.Any.Any= -> Standard.Base.Any.Any