#script6 Complete the exercise only using the core Python language and the scipy stack. The following functions are suggested.
from scipy.io import loadmat as load
from numpy import reshape, array, zeros, log, argmax
from matplotlib.pyplot import figure, plot, legend
def script6():
data = load('seed_data.mat')
c = data['c']
nc = data['nc']
x = data['x']
return
def naivebayes_train(c,nc,x,nk):
pr = []
return pr
def naivebayes_classify(pr,y):
c_hat = []
return c_hat
script6()