Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining

Table 2

Collection evaluation of product styling categories.

Collection evaluation code	Product styling description
Import numpy as np	Taking a spatial
From matplotlib import pyplot as plt	Call back to the main program
Fig = plt.figure()	Data mining time
Ax = plt.axes(projection = “3d”)	The system can afford
X = y = np.arrange(start = −4, stop = 4, step = 0.1)	Of the reduce phase
X, y = np.meshgrid(x, y)	As the starting node
Separate = (distance, distance)	Within the range that
Plt.figure(explode = separate)	Completing a mapreduce process
Plt.pie(sizes, autopct = “%1.1f%%”)	Of storage and processing
Plt.title(“separation distance = 0.8”)	The master will
Plt.show()	The product design points