Issue
I want to calculate Mean Absolute percentage error (MAPE) of predicted and true values. I found a solution from here, but this gives error and shows invalid syntax in the line mask = a <> 0
def mape_vectorized_v2(a, b):
mask = a <> 0
return (np.fabs(a - b)/a)[mask].mean()
def mape_vectorized_v2(a, b):
File "<ipython-input-5-afa5c1162e83>", line 1
def mape_vectorized_v2(a, b):
^
SyntaxError: unexpected EOF while parsing
I am using spyder3. My predicted value is a type np.array and true value is dataframe
type(predicted)
Out[7]: numpy.ndarray
type(y_test)
Out[8]: pandas.core.frame.DataFrame
How do i clear this error and proceed with MAPE Calculation ?
Edit :
predicted.head()
Out[22]:
Total_kWh
0 7.163627
1 6.584960
2 6.638057
3 7.785487
4 6.994427
y_test.head()
Out[23]:
Total_kWh
79 7.2
148 6.7
143 6.7
189 7.2
17 6.4
np.abs(y_test[['Total_kWh']] - predicted[['Total_kWh']]).head()
Out[24]:
Total_kWh
0 NaN
1 NaN
2 NaN
3 NaN
4 0.094427
Solution
In python for compare by not equal need !=
, not <>
.
So need:
def mape_vectorized_v2(a, b):
mask = a != 0
return (np.fabs(a - b)/a)[mask].mean()
Another solution from stats.stackexchange:
def mean_absolute_percentage_error(y_true, y_pred):
y_true, y_pred = np.array(y_true), np.array(y_pred)
return np.mean(np.abs((y_true - y_pred) / y_true)) * 100
Answered By - jezrael
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