# Example of making predictions

# Make a prediction with weights
def predict(row, weights):
	activation = weights[0]
	for i in range(len(row)-1):
		activation += weights[i + 1] * row[i]
	return 1.0 if activation >= 0.0 else 0.0

# test predictions
dataset = [[2.7810836,2.550537003,0],
	[1.465489372,2.362125076,0],
	[3.396561688,4.400293529,0],
	[1.38807019,1.850220317,0],
	[3.06407232,3.005305973,0],
	[7.627531214,2.759262235,1],
	[5.332441248,2.088626775,1],
	[6.922596716,1.77106367,1],
	[8.675418651,-0.242068655,1],
	[7.673756466,3.508563011,1]]
weights = [-0.1, 0.20653640140000007, -0.23418117710000003]
for row in dataset:
	prediction = predict(row, weights)
	print("Expected=%d, Predicted=%d" % (row[-1], prediction))