22202956 - optimised training supervised training

Reinforcement_Learning/Perceptrons.py

@@ -2,7 +2,7 @@ import numpy as np
 import Training_data
 
 rng = np.random.default_rng(123)
-TEACHDATA = 100000
+TEACHDATA = 10000
 TESTDATA = 1000
 # ETA = 0.5
 T_NUMBER = 1  # Number to be detected 0-6

Reinforcement_Learning/Solution_Testing_1.py

 import numpy as np
 
 import Perceptrons
-import PerceptronsSGD
 
 
 def test_function(ETA, p):
@@ -18,13 +17,13 @@ for ETA in ([0.05, 0.1, 0.2, 0.4, 0.75, 1, 2, 5]):  # the list of values for ETA
     x.train(ETA/200)
     y = Perceptrons.SGDPerceptron(20)
     y.train(ETA)
-    for i in range(10):
+    for i in range(1):
         res = test_function(ETA, w)
         print("Thres", res)  # print the results list
-    for i in range(10):
+    for i in range(1):
         res = test_function(ETA/200, x)
         print("Lin", res)  # print the results list
-    for i in range(10):
+    for i in range(1):
         res = test_function(ETA, y)
         print("sgd", res)  # print the results list
     print("\n\n")