Closed
Description
Is your feature request related to a problem? Please describe
currently in classification_report_imbalanced, when setting output_dict to True it ignores the given target_names.
Example:
from pprint import pprint
import numpy as np
from imblearn.metrics import classification_report_imbalanced
y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
target_names = ['class 0', 'class 1', 'class 2']
pprint(classification_report_imbalanced(y_true, y_pred, target_names=target_names, output_dict=1))
Current output:
{0: {'f1': 0.6666666666666666,
'geo': 0.8660254037844386,
'iba': 0.7687499999999998,
'pre': 0.5,
'rec': 1.0,
'spe': 0.75,
'sup': 1},
1: {'f1': 0.0,
'geo': 0.0,
'iba': 0.0,
'pre': 0.0,
'rec': 0.0,
'spe': 0.75,
'sup': 1},
2: {'f1': 0.8,
'geo': 0.816496580927726,
'iba': 0.6444444444444444,
'pre': 1.0,
'rec': 0.6666666666666666,
'spe': 1.0,
'sup': 3},
'avg_f1': 0.6133333333333334,
'avg_geo': 0.6631030293135233,
'avg_iba': 0.5404166666666665,
'avg_pre': 0.7,
'avg_rec': 0.6,
'avg_spe': 0.9,
'total_support': 5}
Describe the solution you'd like
When output_dict=True, set the keys of the returned dict to the corresponding target_names.
Expected output:
{'class 0': {'f1': 0.6666666666666666,
'geo': 0.8660254037844386,
'iba': 0.7687499999999998,
'pre': 0.5,
'rec': 1.0,
'spe': 0.75,
'sup': 1},
'class 1': {'f1': 0.0,
'geo': 0.0,
'iba': 0.0,
'pre': 0.0,
'rec': 0.0,
'spe': 0.75,
'sup': 1},
'class 2': {'f1': 0.8,
'geo': 0.816496580927726,
'iba': 0.6444444444444444,
'pre': 1.0,
'rec': 0.6666666666666666,
'spe': 1.0,
'sup': 3},
'avg_f1': 0.6133333333333334,
'avg_geo': 0.6631030293135233,
'avg_iba': 0.5404166666666665,
'avg_pre': 0.7,
'avg_rec': 0.6,
'avg_spe': 0.9,
'total_support': 5}
Additional context
I think this is important because it will offer a better representation of the output and being helpful for later use, and also I think ignoring target_names silently doesn't make much sense.
Actually, I'll found it even more useful if the last element gets replaced by:
'avg_tot': {'f1': 0.6133333333333334,
'geo': 0.6631030293135233,
'iba': 0.5404166666666665,
'pre': 0.7,
'rec': 0.6,
'spe': 0.9,
'sup': 5},
Instead of:
'avg_f1': 0.6133333333333334,
'avg_geo': 0.6631030293135233,
'avg_iba': 0.5404166666666665,
'avg_pre': 0.7,
'avg_rec': 0.6,
'avg_spe': 0.9,
'total_support': 5}