22202956 - optimised training supervised training

Reinforcement_Learning/Perceptrons.py

@@ -2,10 +2,10 @@ import numpy as np
 import Training_data
 
 rng = np.random.default_rng(123)
-TEACHDATA = 10000
-TESTDATA = 1000
+TEACHDATA = 1000
+TESTDATA = 100
 # ETA = 0.5
-T_NUMBER = 1  # Number to be detected 0-6
+T_NUMBER = 3  # Number to be detected 0-6
 
 
 def sigmoid(val):
@@ -36,7 +36,7 @@ class Neuron:
         for number in range(len(Neuron.test_data)):
             for sample in Neuron.test_data[number]:
                 ix = np.insert(sample.ravel(), 0, 1)
-                res[number] = res[number] + (self.activation(ix.dot(self.weights)))
+                res[number] = res[number] + abs(self.activation(ix.dot(self.weights)))
         return res