masterthesis/codes/node-ranking/churn_rank/20_edges_1619258400.0.txt
Valentin Brandl a3959432d9 Data
2022-04-07 19:34:48 +02:00

131 lines
5.6 KiB
Plaintext

bucket: 2021-04-24 12:00:00+02:00
avg_out: 97.63861386138613
min_out: (RankedNode(Node(1.168.125.94, 7157), 0.5), 0)
max_out: (RankedNode(Node(100.26.179.12, 9796), 0.5), 188)
known_out: Node(34.204.196.211, 9796) 20
1 & 0.32673267 & 0.41366693 & 0.19648853 & 0.25598201 \\
2 & 0.32673267 & 0.41366693 & 0.19648853 & 0.25598201 \\
3 & 0.26277873 & 0.33091943 & 0.15802121 & 0.20477687 \\
4 & 0.26277873 & 0.33091943 & 0.15802121 & 0.20477687 \\
5 & 0.21131053 & 0.26612843 & 0.12707599 & 0.16468344 \\
SR0(0.5): Percentile: 0.0001238131883322785: 10
SR0(0.5): Percentile: 0.00970736168907277: 20
SR0(0.5): Percentile: 0.2248703842308149: 30
SR0(0.5): Percentile: 0.24161304066112654: 40
SR0(0.5): Percentile: 0.24830514680151872: 50
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SR1(0.5): Percentile: 0.2690950657541453: 90
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SR1(0.5): Percentile: 0.2862010652088245: 99
SR2(0.5): Percentile: 0.00010471203781394988: 10
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SR3(0.5): Percentile: 0.00010471203781394988: 10
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SR3(0.5): Percentile: 0.23069809510755554: 99
SR4(0.5): Percentile: 8.37775137184082e-05: 10
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SR4(0.5): Percentile: 0.178627989749186: 95
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PR0(0.5): Percentile: 0.008336754681040085: 10
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PR1(0.5): Percentile: 0.008336754681040085: 10
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PR1(0.5): Percentile: 0.4188150330763149: 80
PR1(0.5): Percentile: 0.4298361823908374: 90
PR1(0.5): Percentile: 0.44073416497619544: 95
PR1(0.5): Percentile: 0.4523815912737997: 99
PR2(0.5): Percentile: 0.007050610546139292: 10
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PR2(0.5): Percentile: 0.32580708996714425: 50
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PR3(0.5): Percentile: 0.007050610546139292: 10
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PR3(0.5): Percentile: 0.32580708996714425: 50
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PR3(0.5): Percentile: 0.36409053999344254: 99
PR4(0.5): Percentile: 0.005641019257039485: 10
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PR4(0.5): Percentile: 0.2619948332681265: 50
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PR4(0.5): Percentile: 0.2714481689707437: 80
PR4(0.5): Percentile: 0.2761831162001691: 90
PR4(0.5): Percentile: 0.2841826976549013: 95
PR4(0.5): Percentile: 0.29272463671699944: 99
avg_out: 97.63861386138613
avg_in: 97.63861386138613
min_in: (RankedNode(Node(121.25.56.135, 7724), 0.5), 1)
max_in: (RankedNode(Node(37.49.230.239, 9159), 0.5), 129)