According to the requirements of the exercise, the polynomial terms should be up to sixth power, which mean transformed into a 28-dimensional vector, but the code provided only consists 11 dimension. I found that this error occurs due to these code (generating polynomials) in the original script:
degree = 5
x1 = data2['Test 1']
x2 = data2['Test 2']
data2.insert(3, 'Ones', 1)
for i in range(1, degree):
for j in range(0, i):
data2['F' + str(i) + str(j)] = np.power(x1, i-j) * np.power(x2, j)
data2.drop('Test 1', axis=1, inplace=True)
data2.drop('Test 2', axis=1, inplace=True)
data2.head()
here I provided my code which could generate the right 28-dimensional vector, which higher the accuracy up to 83.05% (using sklearn package), while original code provided only hit 66.10% when only 11-d vector used as input
max_degree = 6
x1 = data2['Test 1']
x2 = data2['Test 2']
for i in range(2, max_degree + 1):
for j in range(i+1):
data2['x1^' + str(i-j) + '_x2^' + str(j)] = np.power(x1, i-j) * np.power(x2, j)
data2
the result of my code also more readable, here is the column of the data after generated the 28-d vector:
According to the requirements of the exercise, the polynomial terms should be up to sixth power, which mean transformed into a 28-dimensional vector, but the code provided only consists 11 dimension. I found that this error occurs due to these code (generating polynomials) in the original script:
here I provided my code which could generate the right 28-dimensional vector, which higher the accuracy up to 83.05% (using sklearn package), while original code provided only hit 66.10% when only 11-d vector used as input
the result of my code also more readable, here is the column of the data after generated the 28-d vector:
data.columns
Index(['Ones', 'Test 1', 'Test 2', 'Accepted', 'x1^2_x2^0', 'x1^1_x2^1', 'x1^0_x2^2', 'x1^3_x2^0', 'x1^2_x2^1', 'x1^1_x2^2', 'x1^0_x2^3', 'x1^4_x2^0', 'x1^3_x2^1', 'x1^2_x2^2', 'x1^1_x2^3', 'x1^0_x2^4', 'x1^5_x2^0', 'x1^4_x2^1', 'x1^3_x2^2', 'x1^2_x2^3', 'x1^1_x2^4', 'x1^0_x2^5', 'x1^6_x2^0', 'x1^5_x2^1', 'x1^4_x2^2', 'x1^3_x2^3', 'x1^2_x2^4', 'x1^1_x2^5', 'x1^0_x2^6'], dtype='object')