prediction = lnrReg.predict(X_test)
print('RMSE = ', rmse(y_test, prediction))
beg = 0
end = 100
func = lambda i: i if i > 0 else (-1 / i if i < 0 else 1)
lmbd = [func(i) for i in range(beg, end, 1)]
coefs = [[]] * len(lnrReg.coef.arr)
for col in range(0, len(lnrReg.coef.arr)):
coefs[col] = [0] * len(lmbd)
for i in range(beg, end, 1):
lnrReg.L2(X_train, y_train, i)
for j in range(0, len(coefs)):
coefs[j][i] = lnrReg.coef.arr[j][0]
# plt.scatter([row[0] for row in X_test.arr], y_test.arr)
# plt.plot([row[0] for row in X_test.arr], prediction.arr, 'r')
# plt.xlabel('X')
# plt.ylabel('y')
for i in range(0, len(coefs)):
plt.plot(lmbd, coefs[i])
plt.xlabel('lambda')
plt.ylabel('coefficients')
plt.show()
