utils.desirability.DMax(low, high, scale=1, tol=None, missing=None)Implements a desirability function for maximization.
The desirability function assigns a value of 0 for inputs below the low threshold, a value of 1 for inputs above the high threshold, and scales the desirability between 0 and 1 for inputs within the range [low, high] using a specified scale factor.
| Name | Type | Description |
|---|---|---|
| low | float | The lower threshold for the desirability function. |
| high | float | The upper threshold for the desirability function. |
| scale | float | The scaling factor for the desirability function. Must be greater than 0. |
| tol | float | A tolerance value to replace desirability values of 0. Defaults to None. |
| missing | float | The value to use for missing inputs. Defaults to a non-informative value. |
Predicts the desirability values for the given input data.
Plots the desirability function.
Many thanks to Max Kuhn for his implementation of the ‘desirability’ package in R. This class is based on the ‘desirability’ package in R, see: https://cran.r-project.org/package=desirability
from spotdesirability import DMax
import numpy as np
import matplotlib.pyplot as plt
# Create a DMax object
dmax = DMax(low=0, high=10, scale=1)
# Predict desirability for a range of inputs
inputs = np.array([-5, 0, 5, 10, 15])
desirability = dmax.predict(inputs)
print(desirability)
# [0. 0. 0.5 1. 1.]
# Plot the desirability function
dmax.plot()[0. 0. 0.5 1. 1. ]
| Name | Description |
|---|---|
predict |
Predicts the desirability values for the given input data. |