Explain in words the back-propagation neural network algorithm with a bulleted list of steps in an outline fashion, and explain the reason for the last data column in Figure 3.

 

import random from sklearn.cluster import KMeans as kmeans import numpy as np import matplotlib.pyplot as plot DATAPOINTS=20 studentno = 1234567 studentno = int (input( Please enter your student number: )) random.seed (studentno % 10000) coll [random. randint (0, studentno) for i in range (0, DATAPOINTS) ] random.seed (studentno co12 = [random.randint(0, 1000) studentno) for i in range (0, DATAPOINTS) ] 100) random.seed (studentno col3 = [random. randint (0, studentno) for i in range (0, DATAPOINTS)] random.seed (studentno 10) DATAPOINTS)] co15 [random.randint (0, studentno) for i in range (0, DATAPOINTS)] col6 = [i 3 for i in range (0, DATAPOINTS) ] sdata open ( data.txt , [print ( %s, s, 3, 4, o, & (str (coll [1]), str (co12[i]), str (co13[i]), str (co14 [i]), str (co15 [i]), str (col6 [i])), file=sdata) for i in range ( DATAPOINTS)] co14 = [random.randint(0, studentno) for i in range (0,1 random.seed (studentno % 100000) t Figure 3: Data generation algorithm for Practical 2 hand-in