From 64286d6aa65ed2071fcf529a13a795b601937b46 Mon Sep 17 00:00:00 2001
From: George Lacey <490796@hull.ac.uk>
Date: Fri, 10 Feb 2017 12:12:16 +0000
Subject: [PATCH 1/3] Create Dataset class

---
 Dataset.py | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)
 create mode 100644 Dataset.py

diff --git a/Dataset.py b/Dataset.py
new file mode 100644
index 0000000..864ee5b
--- /dev/null
+++ b/Dataset.py
@@ -0,0 +1,16 @@
+from Data import Data
+
+
+class Dataset(object):
+
+    def __init__(self, p_input, p_target):
+        self.inputs = {}
+
+        for index, item in enumerate(p_input):
+            input1 = float(p_input[index].split(',')[0].strip())
+            input2 = float(p_input[index].split(',')[1].strip())
+            if p_target[index] == "1":
+                output = 1
+            else:
+                output = -1
+            self.inputs[index] = Data(input1, input2, output)

From d91911691afddba8a3aba0e2766259135446a8cf Mon Sep 17 00:00:00 2001
From: George Lacey <490796@hull.ac.uk>
Date: Fri, 10 Feb 2017 12:12:44 +0000
Subject: [PATCH 2/3] Implement guess method

---
 Perceptron.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/Perceptron.py b/Perceptron.py
index 327d17e..f499cc0 100644
--- a/Perceptron.py
+++ b/Perceptron.py
@@ -27,6 +27,11 @@ class Perceptron(object):
             print("Total = %f" % input)
 
             if input > 0:
-                return True
+                return 1
             else:
-                return False
+                return -1
+
+        def guess(self, p_desired):
+            prediction = float(self.activation())
+            return p_desired - prediction
+

From e4accc5927f73fa34444ed0f4ff9d838b15bf724 Mon Sep 17 00:00:00 2001
From: George Lacey <georgelaceyy@gmail.com>
Date: Fri, 10 Feb 2017 12:16:53 +0000
Subject: [PATCH 3/3] Add Main

---
 Main.py | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/Main.py b/Main.py
index e69de29..7bcc4db 100644
--- a/Main.py
+++ b/Main.py
@@ -0,0 +1,16 @@
+from Perceptron import Perceptron
+from random import Random
+from Dataset import Dataset
+
+rand = Random()
+data = Dataset(open("input.txt").read().split('\n'), open("target.txt").read().split('\n'))
+
+
+for key in data.inputs:
+    i = data.inputs
+    print("v1: ", i[key].value1, "v2: ", i[key].value2, "target: ", i[key].target)
+    p = Perceptron()
+    p.add_input("1", i[key].value1, rand.uniform(-1, 1))
+    p.add_input("2", i[key].value2, rand.uniform(-1, 1))
+    p.add_input("bias", 1, rand.uniform(-1, 1))
+    print("%f" % p.guess(i[key].target))