Merge branch 'master' of git.njae.me.uk:national-cipher-challenge

[cipher-tools.git] / caesar_break_parameter_trials.csv

diff --git a/caesar_break_parameter_trials.csv b/caesar_break_parameter_trials.csv
index ae1b8415f1b65f23a0c263e744cd61ccce40d486..e18f92c5604d97855b83cff0fdce99d17c7385a1 100644 (file)
--- a/caesar_break_parameter_trials.csv
+++ b/caesar_break_parameter_trials.csv
@@ -1,148 +1,106 @@
-metric,scaling,message_length,score
-l1, normalised, 300, 0.9996
-l1, normalised, 100, 1.0
-l1, normalised, 50, 0.9988
-l1, normalised, 30, 0.99
-l1, normalised, 20, 0.952
-l1, normalised, 10, 0.7144
-l1, normalised, 5, 0.4368
-l1, euclidean_scaled, 300, 0.999
-l1, euclidean_scaled, 100, 0.9994
-l1, euclidean_scaled, 50, 0.9984
-l1, euclidean_scaled, 30, 0.9912
-l1, euclidean_scaled, 20, 0.9526
-l1, euclidean_scaled, 10, 0.7478
-l1, euclidean_scaled, 5, 0.439
-l1, normalised_with_identity, 300, 0.9652
-l1, normalised_with_identity, 100, 0.9898
-l1, normalised_with_identity, 50, 0.9862
-l1, normalised_with_identity, 30, 0.9622
-l1, normalised_with_identity, 20, 0.9084
-l1, normalised_with_identity, 10, 0.7134
-l1, normalised_with_identity, 5, 0.4376
-l2, normalised, 300, 0.9994
-l2, normalised, 100, 0.9994
-l2, normalised, 50, 0.999
-l2, normalised, 30, 0.9808
-l2, normalised, 20, 0.9364
-l2, normalised, 10, 0.7062
-l2, normalised, 5, 0.4304
-l2, euclidean_scaled, 300, 0.9994
-l2, euclidean_scaled, 100, 0.9996
-l2, euclidean_scaled, 50, 0.9978
-l2, euclidean_scaled, 30, 0.9842
-l2, euclidean_scaled, 20, 0.9372
-l2, euclidean_scaled, 10, 0.7214
-l2, euclidean_scaled, 5, 0.4402
-l2, normalised_with_identity, 300, 0.9992
-l2, normalised_with_identity, 100, 0.9992
-l2, normalised_with_identity, 50, 0.9966
-l2, normalised_with_identity, 30, 0.9848
-l2, normalised_with_identity, 20, 0.9346
-l2, normalised_with_identity, 10, 0.719
-l2, normalised_with_identity, 5, 0.428
-l2, normalised, 300, 0.9994
-l2, normalised, 100, 0.9994
-l2, normalised, 50, 0.9928
-l2, normalised, 30, 0.9554
-l2, normalised, 20, 0.8642
-l2, normalised, 10, 0.5982
-l2, normalised, 5, 0.3996
-l2, euclidean_scaled, 300, 0.9998
-l2, euclidean_scaled, 100, 0.9998
-l2, euclidean_scaled, 50, 0.994
-l2, euclidean_scaled, 30, 0.9692
-l2, euclidean_scaled, 20, 0.8902
-l2, euclidean_scaled, 10, 0.6312
-l2, euclidean_scaled, 5, 0.3964
-l2, normalised_with_identity, 300, 0.9996
-l2, normalised_with_identity, 100, 0.9976
-l2, normalised_with_identity, 50, 0.9702
-l2, normalised_with_identity, 30, 0.8988
-l2, normalised_with_identity, 20, 0.7732
-l2, normalised_with_identity, 10, 0.5536
-l2, normalised_with_identity, 5, 0.3958
-cosine_distance, normalised, 300, 1.0
-cosine_distance, normalised, 100, 0.9992
-cosine_distance, normalised, 50, 0.9978
-cosine_distance, normalised, 30, 0.9862
-cosine_distance, normalised, 20, 0.938
-cosine_distance, normalised, 10, 0.7216
-cosine_distance, normalised, 5, 0.4358
-cosine_distance, euclidean_scaled, 300, 1.0
-cosine_distance, euclidean_scaled, 100, 0.9996
-cosine_distance, euclidean_scaled, 50, 0.9986
-cosine_distance, euclidean_scaled, 30, 0.9856
-cosine_distance, euclidean_scaled, 20, 0.9348
-cosine_distance, euclidean_scaled, 10, 0.7036
-cosine_distance, euclidean_scaled, 5, 0.4402
-cosine_distance, normalised_with_identity, 300, 0.999
-cosine_distance, normalised_with_identity, 100, 0.9994
-cosine_distance, normalised_with_identity, 50, 0.9984
-cosine_distance, normalised_with_identity, 30, 0.9844
-cosine_distance, normalised_with_identity, 20, 0.9376
-cosine_distance, normalised_with_identity, 10, 0.7184
-cosine_distance, normalised_with_identity, 5, 0.442
-harminic_mean, normalised, 300, 0.8082
-harminic_mean, normalised, 100, 0.8386
-harminic_mean, normalised, 50, 0.7576
-harminic_mean, normalised, 30, 0.2696
-harminic_mean, normalised, 20, 0.8576
-harminic_mean, normalised, 10, 0.6748
-harminic_mean, normalised, 5, 0.4498
-harminic_mean, euclidean_scaled, 300, 0.4754
-harminic_mean, euclidean_scaled, 100, 0.5136
-harminic_mean, euclidean_scaled, 50, 0.6756
-harminic_mean, euclidean_scaled, 30, 0.596
-harminic_mean, euclidean_scaled, 20, 0.538
-harminic_mean, euclidean_scaled, 10, 0.4296
-harminic_mean, euclidean_scaled, 5, 0.357
-harminic_mean, normalised_with_identity, 300, 0.9544
-harminic_mean, normalised_with_identity, 100, 0.9738
-harminic_mean, normalised_with_identity, 50, 0.952
-harminic_mean, normalised_with_identity, 30, 0.9252
-harminic_mean, normalised_with_identity, 20, 0.8956
-harminic_mean, normalised_with_identity, 10, 0.747
-harminic_mean, normalised_with_identity, 5, 0.4582
-geometric_mean, normalised, 300, 0.9996
-geometric_mean, normalised, 100, 0.9996
-geometric_mean, normalised, 50, 0.989
-geometric_mean, normalised, 30, 0.9218
-geometric_mean, normalised, 20, 0.9434
-geometric_mean, normalised, 10, 0.7138
-geometric_mean, normalised, 5, 0.4626
-geometric_mean, euclidean_scaled, 300, 0.9998
-geometric_mean, euclidean_scaled, 100, 0.9986
-geometric_mean, euclidean_scaled, 50, 0.993
-geometric_mean, euclidean_scaled, 30, 0.9538
-geometric_mean, euclidean_scaled, 20, 0.8868
-geometric_mean, euclidean_scaled, 10, 0.6452
-geometric_mean, euclidean_scaled, 5, 0.4466
-geometric_mean, normalised_with_identity, 300, 0.9416
-geometric_mean, normalised_with_identity, 100, 0.9894
-geometric_mean, normalised_with_identity, 50, 0.9854
-geometric_mean, normalised_with_identity, 30, 0.9758
-geometric_mean, normalised_with_identity, 20, 0.9336
-geometric_mean, normalised_with_identity, 10, 0.7704
-geometric_mean, normalised_with_identity, 5, 0.4742
-inverse_log_pl, normalised, 300, 0.9994
-inverse_log_pl, normalised, 100, 0.9992
-inverse_log_pl, normalised, 50, 0.9998
-inverse_log_pl, normalised, 30, 0.9974
-inverse_log_pl, normalised, 20, 0.9804
-inverse_log_pl, normalised, 10, 0.8164
-inverse_log_pl, normalised, 5, 0.4832
-inverse_log_pl, euclidean_scaled, 300, 0.9996
-inverse_log_pl, euclidean_scaled, 100, 0.9994
-inverse_log_pl, euclidean_scaled, 50, 0.9998
-inverse_log_pl, euclidean_scaled, 30, 0.9968
-inverse_log_pl, euclidean_scaled, 20, 0.98
-inverse_log_pl, euclidean_scaled, 10, 0.8116
-inverse_log_pl, euclidean_scaled, 5, 0.4824
-inverse_log_pl, normalised_with_identity, 300, 0.9994
-inverse_log_pl, normalised_with_identity, 100, 0.9996
-inverse_log_pl, normalised_with_identity, 50, 0.9994
-inverse_log_pl, normalised_with_identity, 30, 0.996
-inverse_log_pl, normalised_with_identity, 20, 0.9796
-inverse_log_pl, normalised_with_identity, 10, 0.8148
-inverse_log_pl, normalised_with_identity, 5, 0.477
+<<<<<<< HEAD
+,message_length
+scoring, 300, 100, 50, 30, 20, 10, 5
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+Pletters, 0.9994, 0.9994, 0.9994, 0.9966, 0.9778, 0.8174, 0.4712
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + euclidean_scaled, 0.9996, 0.9996, 0.9974, 0.9836, 0.9356, 0.7124, 0.4218
+cosine_distance + normalised, 0.9994, 0.9996, 0.998, 0.9836, 0.934, 0.7186, 0.4402
+cosine_distance + normalised, 0.9994, 0.9996, 0.998, 0.9836, 0.934, 0.7186, 0.4402
+cosine_distance + normalised, 0.9994, 0.9996, 0.998, 0.9836, 0.934, 0.7186, 0.4402
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+cosine_distance + normalised, 0.9994, 0.9996, 0.998, 0.9836, 0.934, 0.7186, 0.4402
+cosine_distance + normalised, 0.9994, 0.9996, 0.998, 0.9836, 0.934, 0.7186, 0.4402
+cosine_distance + normalised, 0.9994, 0.9996, 0.998, 0.9836, 0.934, 0.7186, 0.4402
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + euclidean_scaled, 0.9996, 0.9996, 0.99, 0.9506, 0.8892, 0.6562, 0.4368
+geometric_mean + normalised, 0.9996, 0.9992, 0.9902, 0.9222, 0.9408, 0.7062, 0.4568
+geometric_mean + normalised, 0.9996, 0.9992, 0.9902, 0.9222, 0.9408, 0.7062, 0.4568
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+geometric_mean + normalised, 0.9996, 0.9992, 0.9902, 0.9222, 0.9408, 0.7062, 0.4568
+harmonic_mean + euclidean_scaled, 0.4688, 0.5122, 0.6894, 0.5948, 0.5258, 0.4426, 0.3642
+harmonic_mean + euclidean_scaled, 0.4688, 0.5122, 0.6894, 0.5948, 0.5258, 0.4426, 0.3642
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+harmonic_mean + euclidean_scaled, 0.4688, 0.5122, 0.6894, 0.5948, 0.5258, 0.4426, 0.3642
+harmonic_mean + normalised, 0.8134, 0.8368, 0.7672, 0.2674, 0.8608, 0.6736, 0.453
+harmonic_mean + normalised, 0.8134, 0.8368, 0.7672, 0.2674, 0.8608, 0.6736, 0.453
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+l1 + euclidean_scaled, 0.9998, 0.9994, 0.9984, 0.9904, 0.9502, 0.7558, 0.4348
+l1 + euclidean_scaled, 0.9998, 0.9994, 0.9984, 0.9904, 0.9502, 0.7558, 0.4348
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+l1 + euclidean_scaled, 0.9998, 0.9994, 0.9984, 0.9904, 0.9502, 0.7558, 0.4348
+l1 + euclidean_scaled, 0.9998, 0.9994, 0.9984, 0.9904, 0.9502, 0.7558, 0.4348
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+l2 + euclidean_scaled, 0.9996, 0.9988, 0.9992, 0.9786, 0.9368, 0.712, 0.4336
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+l3 + euclidean_scaled, 0.9996, 0.999, 0.996, 0.9684, 0.8934, 0.6282, 0.4084
+l3 + euclidean_scaled, 0.9996, 0.999, 0.996, 0.9684, 0.8934, 0.6282, 0.4084
+l3 + euclidean_scaled, 0.9996, 0.999, 0.996, 0.9684, 0.8934, 0.6282, 0.4084
+l3 + euclidean_scaled, 0.9996, 0.999, 0.996, 0.9684, 0.8934, 0.6282, 0.4084
+l3 + euclidean_scaled, 0.9996, 0.999, 0.996, 0.9684, 0.8934, 0.6282, 0.4084
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+l3 + normalised, 1.0, 0.9986, 0.9932, 0.963, 0.8696, 0.594, 0.4122
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+l3 + normalised, 1.0, 0.9986, 0.9932, 0.963, 0.8696, 0.594, 0.4122
+l3 + normalised, 1.0, 0.9986, 0.9932, 0.963, 0.8696, 0.594, 0.4122
+=======
+"name",100,50,30,20,10,5\r
+"Pletters",4996,4997,4984,4900,4063,2358\r
+"cosine_similarity + euclidean_scaled",4998,4986,4914,4659,3528,2198\r
+"cosine_similarity + normalised",4997,4993,4917,4659,3557,2084\r
+"l1 + euclidean_scaled",4998,4992,4951,4755,3767,2192\r
+"l1 + normalised",4998,4996,4936,4767,3596,2161\r
+"l2 + euclidean_scaled",4998,4990,4926,4683,3567,2179\r
+"l2 + normalised",4995,4993,4920,4672,3610,2135\r
+"l3 + euclidean_scaled",4996,4964,4822,4457,3167,2018\r
+"l3 + normalised",4999,4973,4797,4351,2872,1989\r
+>>>>>>> 883806c... More tweaking