def main():
#load dataset
data = pd.read_csv('../data/iris.data', sep=',', header=0)
#classifying with two classes only
dataset = data[data['CLASS'] != 'Iris-virginica']
#using the LENGHTS for separation
X = dataset[['SEPAL_LENGHT','PETAL_LENGHT']]
#converting classes to -1 and 1
y = dataset['CLASS'].apply(convert)
#train Perceptron
model = Perceptron(X.shape[1])
model.fit(X,y)
#plotting
w = model.get_w()
#decision boundary: w[0] + w[1]*x + w[2]*y = 0
x1 = np.linspace(0, 10, 100)
x2 = -w[0]/w[2] - (w[1]/w[2])*x1
plt.plot(x1,x2,'k')
plt.scatter(X['SEPAL_LENGHT'],X['PETAL_LENGHT'])
plt.show()
