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{
"overview": {
"concept_group_names": [
"category",
"sleeve_length",
"pattern"
],
"metrics": {
"prec_rec_f1": {
"type": "table",
"value": {
"header": [
"precision",
"recall",
"f1-score",
"support"
],
"data": [
[
0.66,
1.0,
0.75,
222
],
[
1.0,
1.0,
0.75,
222
]
],
"summary": {
"mean / total": [
0.66,
1.0,
0.75,
222
],
"weighted mean / total": [
0.66,
1.0,
0.75,
222
]
}
}
}
}
},
"results": [
{
"concept_group_name": "sleeve_length",
"concept_names": [
"long",
"medium",
"short"
],
"metrics": {
"precision_recall_f1": {
"type": "table",
"condition": {
"threshold": 0.5,
"min_recall": 0.6
},
"table_value": {
"header": [
"precision",
"recall",
"f1-score",
"support"
],
"summary": {
"mean / total": [
0.66,
1.0,
0.75,
88
],
"weighted mean / total": [
0.66,
1.0,
0.75,
88
]
},
"data": [
[
0.66,
1.0,
0.75,
88
],
[
0.66,
1.0,
0.75,
88
]
]
}
}
}
}
]
}
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