Update hierarchical precision and recall values in tests.py
Browse files
tests.py
CHANGED
@@ -10,12 +10,14 @@ test_cases = [
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"1111",
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"1111",
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"1111",
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],
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"predictions": [
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"1111",
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"1112",
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"1120",
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"1211",
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"2111",
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"111",
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"11",
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@@ -24,9 +26,9 @@ test_cases = [
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],
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"result": {
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"accuracy": 0.1111111111111111,
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-
"hierarchical_precision": 0.
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"hierarchical_recall": 1.0,
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"hierarchical_fmeasure": 0.
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},
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},
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{
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@@ -44,9 +46,9 @@ test_cases = [
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"predictions": ["1112"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.
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"hierarchical_recall": 0.
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"hierarchical_fmeasure": 0.
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},
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},
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{
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@@ -54,9 +56,9 @@ test_cases = [
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"predictions": ["1120"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.
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"hierarchical_recall": 0.
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"hierarchical_fmeasure": 0.
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},
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},
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{
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@@ -69,14 +71,24 @@ test_cases = [
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"hierarchical_fmeasure": 0.25,
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},
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},
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{
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"references": ["1111"],
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"predictions": ["2111"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.
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"hierarchical_recall": 0.
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"hierarchical_fmeasure": 0
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},
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},
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{
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@@ -84,9 +96,9 @@ test_cases = [
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"predictions": ["111"],
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"result": {
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"accuracy": 0.0,
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-
"hierarchical_precision": 0
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-
"hierarchical_recall": 0.
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-
"hierarchical_fmeasure": 0.
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},
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},
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{
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@@ -94,9 +106,9 @@ test_cases = [
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"predictions": ["11"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0
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"hierarchical_recall": 0.
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"hierarchical_fmeasure": 0.
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},
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},
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{
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@@ -104,9 +116,19 @@ test_cases = [
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"predictions": ["1"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0
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"hierarchical_recall": 0.
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"hierarchical_fmeasure": 0.
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},
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},
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]
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"1111",
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"1111",
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"1111",
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+
"1111",
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],
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"predictions": [
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"1111",
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"1112",
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"1120",
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"1211",
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"1311",
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"2111",
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"111",
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"11",
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],
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"result": {
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"accuracy": 0.1111111111111111,
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+
"hierarchical_precision": 0.26666666666666666,
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"hierarchical_recall": 1.0,
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"hierarchical_fmeasure": 0.4210526315789474,
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},
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},
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{
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"predictions": ["1112"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.75,
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"hierarchical_recall": 0.75,
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"hierarchical_fmeasure": 0.75,
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},
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},
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{
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"predictions": ["1120"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.5,
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"hierarchical_recall": 0.5,
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"hierarchical_fmeasure": 0.5,
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},
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},
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{
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"hierarchical_fmeasure": 0.25,
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},
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},
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{
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"references": ["1111"],
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"predictions": ["1311"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.25,
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"hierarchical_recall": 0.25,
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"hierarchical_fmeasure": 0.25,
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},
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},
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{
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"references": ["1111"],
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"predictions": ["2111"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.0,
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"hierarchical_recall": 0.0,
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"hierarchical_fmeasure": 0,
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},
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},
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{
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"predictions": ["111"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 1.0,
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"hierarchical_recall": 0.25,
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"hierarchical_fmeasure": 0.4,
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},
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},
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{
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"predictions": ["11"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 1.0,
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"hierarchical_recall": 0.25,
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"hierarchical_fmeasure": 0.4,
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},
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},
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{
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"predictions": ["1"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 1.0,
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"hierarchical_recall": 0.25,
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"hierarchical_fmeasure": 0.4,
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},
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},
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{
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"references": ["1111"],
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"predictions": ["9999"],
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"result": {
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"accuracy": 0.0,
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"hierarchical_precision": 0.0,
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"hierarchical_recall": 0.0,
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"hierarchical_fmeasure": 0,
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},
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},
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]
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