From 6d77432628eef8d784d29ae4255909c4fd04dcf9 Mon Sep 17 00:00:00 2001
From: Michael Mutote <130656746+mr1Michael@users.noreply.github.com>
Date: Thu, 23 Nov 2023 14:35:47 +0100
Subject: [PATCH] 22202956 - optimised training supervised training
---
Reinforcement_Learning/Perceptrons.py | 2 +-
Reinforcement_Learning/Solution_Testing_1.py | 7 +++----
2 files changed, 4 insertions(+), 5 deletions(-)
diff --git a/Reinforcement_Learning/Perceptrons.py b/Reinforcement_Learning/Perceptrons.py
index 30a2974..a1ad48e 100644
--- a/Reinforcement_Learning/Perceptrons.py
+++ b/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
diff --git a/Reinforcement_Learning/Solution_Testing_1.py b/Reinforcement_Learning/Solution_Testing_1.py
index 1153878..0b07b7c 100644
--- a/Reinforcement_Learning/Solution_Testing_1.py
+++ b/Reinforcement_Learning/Solution_Testing_1.py
@@ -1,7 +1,6 @@
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")
--
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