text: from sklearn.preprocessing import LabelEncoder
  import numpy as np
  import matplotlib.pyplot as plt
  #import seaborn as sb
  
  
  conf = np.loadtxt('Files/confusion.csv', delimiter = ',')
  
  classes = ['STAR', 'GALAXY', 'QSO', 'Unknown']
  
  actual = [[row[i] for row in conf] for i in range(len(classes))]
  
  a = ['Matt', 'Chris', 'Chris', 'Matt', 'Chris']
  
  hot = LabelEncoder()
  
  print(hot.fit_transform(a))
  
  #actual = actual.reshape
  
  ax, fig = plt.subplots()