transformers

Media transformation functions for Marketing Mix Models.

Functions

batched_convolution(x, w[, axis, mode])	Apply a 1D convolution in a vectorized way across multiple batch dimensions.
delayed_adstock(x[, alpha, theta, l_max, ...])	Delayed adstock transformation.
geometric_adstock(x[, alpha, l_max, ...])	Geometric adstock transformation.
hill_function(x, slope, kappa)	Hill Function.
hill_saturation_sigmoid(x, sigma, beta, lam)	Hill Saturation Sigmoid Function.
inverse_scaled_logistic_saturation(x[, lam, eps])	Inverse scaled logistic saturation transformation.
logistic_saturation(x[, lam])	Logistic saturation transformation.
michaelis_menten(x, alpha, lam)	Evaluate the Michaelis-Menten function for given values of x, alpha, and lambda.
root_saturation(x, alpha)	Root saturation transformation.
tanh_saturation(x[, b, c])	Tanh saturation transformation.
tanh_saturation_baselined(x, x0[, gain, r])	Baselined Tanh Saturation.
weibull_adstock(x[, lam, k, l_max, axis, ...])	Weibull Adstocking Transformation.

Classes

ConvMode(value)	Convolution mode for the convolution.
TanhSaturationBaselinedParameters(x0, gain, r)	Representation of tanh saturation parameters in baselined form.
TanhSaturationParameters(b, c)	Container for tanh saturation parameters.
WeibullType(value)	Weibull type for the Weibull adstock.