Ns = [5, 10, 15, 20]
large_dataset_precisions = {
'SKBPR-BC': (Ns, [0.0366, 0.0297, 0.0263,
0.0244], [0.0004, 0.0003, 0.0002,
0.0002], [0.0002, 0.0003, 0.0003, 0.0003]),
'SKBPR-BC-SEQ': (Ns, [0.0363, 0.0293, 0.0260,
0.0241], [0.0001, 0.0002, 0.0003,
0.0002], [0.0003, 0.0002, 0.0003, 0.0002]),
}
large_dataset_recalls = {
'SKBPR-BC': (Ns, [0.0844, 0.1139, 0.1367,
0.1559], [0.0011, 0.0010, 0.0010,
0.0006], [0.0011, 0.0011, 0.0006, 0.0004]),
'SKBPR-BC-SEQ': (Ns, [0.0855, 0.1154, 0.1384,
0.1578], [0.0005, 0.0006, 0.0007,
0.0006], [0.0007, 0.0006, 0.0009, 0.0010]),
}
if __name__ == '__main__':
precision_axis = [0, 25, 0.020, 0.040]
recall_axis = [0, 25, 0.06, 0.20]
# draw precision and recall on on graph
# omit results of small datasets
mixed_datasets = [
('Precision', 'Large', precision_axis, large_dataset_precisions),
('Recall', 'Large', recall_axis, large_dataset_recalls),
]
output_graph(mixed_datasets, 'output/sequence_precision_recall.png')
'Hottest': (Ns, [0.0217, 0.0149, 0.0132, 0.0130], [0.0001, 0.0003, 0.0000, 0.0000], [0.0005, 0.0008, 0.0003, 0.0002]),
'SKBPR-BC': (Ns, [0.0366, 0.0297, 0.0263, 0.0244], [0.0004, 0.0003, 0.0002, 0.0002], [0.0002, 0.0003, 0.0003, 0.0003]),
'SKBPR-BCIPF': (Ns, [0.0401, 0.0321, 0.0281, 0.0259], [0.0004, 0.0003, 0.0002, 0.0001], [0.0002, 0.0002, 0.0004, 0.0003]),
}
small_dataset_recalls = {
'Hottest': (Ns, [0.1256, 0.1567, 0.2122, 0.2569], [0.0212, 0.0013, 0.0141, 0.0098], [0.0031, 0.0003, 0.0079, 0.0067]),
'SKBPR-BC': (Ns, [0.1105, 0.1664, 0.2104, 0.2517], [0.0040, 0.0016, 0.0023, 0.0011], [0.0025, 0.0014, 0.0034, 0.0020]),
'SKBPR-BCIPF': (Ns, [0.1157, 0.1790, 0.2268, 0.2669], [0.0025, 0.0014, 0.0014, 0.0025], [0.0017, 0.0011, 0.0009, 0.0015]),
}
large_dataset_recalls = {
'Hottest': (Ns, [0.0526, 0.0792, 0.0979, 0.1003], [0.0009, 0.0037, 0.0029, 0.0021], [0.0002, 0.0016, 0.0004, 0.0004]),
'SKBPR-BC': (Ns, [0.0844, 0.1139, 0.1367, 0.1559], [0.0011, 0.0010, 0.0010, 0.0006], [0.0011, 0.0011, 0.0006, 0.0004]),
'SKBPR-BCIPF': (Ns, [0.0955, 0.1286, 0.1522, 0.1726], [0.0007, 0.0012, 0.0013, 0.0006], [0.0009, 0.0013, 0.0017, 0.0008]),
}
if __name__ == '__main__':
precision_axis = [0, 25, 0.010, 0.070]
precision_datasets = [
('Precision', 'Small', precision_axis, small_dataset_precisions),
('Precision', 'Large', precision_axis, large_dataset_precisions),
]
output_graph(precision_datasets, 'output/basic_precision.png')
recall_axis = [0, 25, 0.04, 0.35]
recall_datasets = [
('Recall', 'Small', recall_axis, small_dataset_recalls),
('Recall', 'Large', recall_axis, large_dataset_recalls),
]
output_graph(recall_datasets, 'output/basic_recall.png')
from plot_common import output_graph
# results of N = 5, 10, 15, 20
Ns = [5, 10, 15, 20]
large_dataset_precisions = {
'SKBPR-BCIPF': (Ns, [0.0401, 0.0321, 0.0281, 0.0259], [0.0004, 0.0003, 0.0002, 0.0001], [0.0002, 0.0002, 0.0004, 0.0003]),
'SKBPR-BCIPF-FB': (Ns, [0.0370, 0.0283, 0.0242, 0.0219], [0.0001, 0.0002, 0.0002, 0.0001], [0.0003, 0.0001, 0.0003, 0.0001]),
}
large_dataset_recalls = {
'SKBPR-BCIPF': (Ns, [0.0955, 0.1286, 0.1522, 0.1726], [0.0007, 0.0012, 0.0013, 0.0006], [0.0009, 0.0013, 0.0017, 0.0008]),
'SKBPR-BCIPF-FB': (Ns, [0.0974, 0.1309, 0.1546, 0.1752], [0.0008, 0.0012, 0.0013, 0.0006], [0.0009, 0.0012, 0.0017, 0.0008]),
}
if __name__ == '__main__':
precision_axis = [0, 25, 0.010, 0.050]
recall_axis = [0, 25, 0.04, 0.25]
# draw precision and recall on on graph
# omit results of small datasets
mixed_datasets = [
('Precision', 'Large', precision_axis, large_dataset_precisions),
('Recall', 'Large', recall_axis, large_dataset_recalls),
]
output_graph(mixed_datasets, 'output/fallback_precision_recall.png')
'SKBPR-BCIPF': (Ns, [0.1157, 0.1790, 0.2268,
0.2669], [0.0025, 0.0014, 0.0014,
0.0025], [0.0017, 0.0011, 0.0009, 0.0015]),
}
large_dataset_recalls = {
'Hottest': (Ns, [0.0526, 0.0792, 0.0979,
0.1003], [0.0009, 0.0037, 0.0029,
0.0021], [0.0002, 0.0016, 0.0004, 0.0004]),
'SKBPR-BC': (Ns, [0.0844, 0.1139, 0.1367,
0.1559], [0.0011, 0.0010, 0.0010,
0.0006], [0.0011, 0.0011, 0.0006, 0.0004]),
'SKBPR-BCIPF': (Ns, [0.0955, 0.1286, 0.1522,
0.1726], [0.0007, 0.0012, 0.0013,
0.0006], [0.0009, 0.0013, 0.0017, 0.0008]),
}
if __name__ == '__main__':
precision_axis = [0, 25, 0.010, 0.070]
precision_datasets = [
('Precision', 'Small', precision_axis, small_dataset_precisions),
('Precision', 'Large', precision_axis, large_dataset_precisions),
]
output_graph(precision_datasets, 'output/basic_precision.png')
recall_axis = [0, 25, 0.04, 0.35]
recall_datasets = [
('Recall', 'Small', recall_axis, small_dataset_recalls),
('Recall', 'Large', recall_axis, large_dataset_recalls),
]
output_graph(recall_datasets, 'output/basic_recall.png')
[0.0001, 0.0002, 0.0003, 0.0002],
[0.0003, 0.0002, 0.0003, 0.0002],
),
}
large_dataset_recalls = {
"SKBPR-BC": (
Ns,
[0.0844, 0.1139, 0.1367, 0.1559],
[0.0011, 0.0010, 0.0010, 0.0006],
[0.0011, 0.0011, 0.0006, 0.0004],
),
"SKBPR-BC-SEQ": (
Ns,
[0.0855, 0.1154, 0.1384, 0.1578],
[0.0005, 0.0006, 0.0007, 0.0006],
[0.0007, 0.0006, 0.0009, 0.0010],
),
}
if __name__ == "__main__":
precision_axis = [0, 25, 0.020, 0.040]
recall_axis = [0, 25, 0.06, 0.20]
# draw precision and recall on on graph
# omit results of small datasets
mixed_datasets = [
("Precision", "Large", precision_axis, large_dataset_precisions),
("Recall", "Large", recall_axis, large_dataset_recalls),
]
output_graph(mixed_datasets, "output/sequence_precision_recall.png")
