Finished for a bit

[cipher-tools.git] / caesar_break_parameter_trials.csv

diff --git a/caesar_break_parameter_trials.csv b/caesar_break_parameter_trials.csv
index ba7ee273a0682301beab9d4da6d0db1cba45f0ec..465cb85fd81d9dc6365a40883134c0ba48015b13 100644 (file)
--- a/caesar_break_parameter_trials.csv
+++ b/caesar_break_parameter_trials.csv
@@ -1,168 +1,23 @@
-l1, normalised_english_counts, normalise, 300, 0.9992
-l1, normalised_english_counts, normalise, 100, 0.9996
-l1, normalised_english_counts, normalise, 50, 0.9992
-l1, normalised_english_counts, normalise, 30, 0.9914
-l1, normalised_english_counts, normalise, 20, 0.9532
-l1, normalised_english_counts, normalise, 10, 0.7442
-l1, normalised_english_counts, normalise, 5, 0.4358
-l1, normalised_english_counts, scale, 300, 1.0
-l1, normalised_english_counts, scale, 100, 0.999
-l1, normalised_english_counts, scale, 50, 0.9988
-l1, normalised_english_counts, scale, 30, 0.9848
-l1, normalised_english_counts, scale, 20, 0.9316
-l1, normalised_english_counts, scale, 10, 0.715
-l1, normalised_english_counts, scale, 5, 0.436
-l1, scaled_english_counts, normalise, 300, 0.9994
-l1, scaled_english_counts, normalise, 100, 0.9998
-l1, scaled_english_counts, normalise, 50, 0.999
-l1, scaled_english_counts, normalise, 30, 0.9868
-l1, scaled_english_counts, normalise, 20, 0.9482
-l1, scaled_english_counts, normalise, 10, 0.7434
-l1, scaled_english_counts, normalise, 5, 0.4532
-l1, scaled_english_counts, scale, 300, 0.9996
-l1, scaled_english_counts, scale, 100, 1.0
-l1, scaled_english_counts, scale, 50, 0.9988
-l1, scaled_english_counts, scale, 30, 0.9874
-l1, scaled_english_counts, scale, 20, 0.9488
-l1, scaled_english_counts, scale, 10, 0.745
-l1, scaled_english_counts, scale, 5, 0.4548
-l2, normalised_english_counts, normalise, 300, 0.9994
-l2, normalised_english_counts, normalise, 100, 0.9992
-l2, normalised_english_counts, normalise, 50, 0.9978
-l2, normalised_english_counts, normalise, 30, 0.9836
-l2, normalised_english_counts, normalise, 20, 0.9318
-l2, normalised_english_counts, normalise, 10, 0.7072
-l2, normalised_english_counts, normalise, 5, 0.4294
-l2, normalised_english_counts, scale, 300, 0.9988
-l2, normalised_english_counts, scale, 100, 0.9998
-l2, normalised_english_counts, scale, 50, 0.9978
-l2, normalised_english_counts, scale, 30, 0.9868
-l2, normalised_english_counts, scale, 20, 0.9364
-l2, normalised_english_counts, scale, 10, 0.7136
-l2, normalised_english_counts, scale, 5, 0.446
-l2, scaled_english_counts, normalise, 300, 0.9992
-l2, scaled_english_counts, normalise, 100, 0.9996
-l2, scaled_english_counts, normalise, 50, 0.9984
-l2, scaled_english_counts, normalise, 30, 0.9854
-l2, scaled_english_counts, normalise, 20, 0.9328
-l2, scaled_english_counts, normalise, 10, 0.7122
-l2, scaled_english_counts, normalise, 5, 0.4328
-l2, scaled_english_counts, scale, 300, 1.0
-l2, scaled_english_counts, scale, 100, 0.9998
-l2, scaled_english_counts, scale, 50, 0.9972
-l2, scaled_english_counts, scale, 30, 0.9842
-l2, scaled_english_counts, scale, 20, 0.9356
-l2, scaled_english_counts, scale, 10, 0.7126
-l2, scaled_english_counts, scale, 5, 0.4318
-l3, normalised_english_counts, normalise, 300, 0.9996
-l3, normalised_english_counts, normalise, 100, 0.999
-l3, normalised_english_counts, normalise, 50, 0.994
-l3, normalised_english_counts, normalise, 30, 0.9658
-l3, normalised_english_counts, normalise, 20, 0.8926
-l3, normalised_english_counts, normalise, 10, 0.6252
-l3, normalised_english_counts, normalise, 5, 0.3974
-l3, normalised_english_counts, scale, 300, 0.9996
-l3, normalised_english_counts, scale, 100, 0.998
-l3, normalised_english_counts, scale, 50, 0.9828
-l3, normalised_english_counts, scale, 30, 0.9334
-l3, normalised_english_counts, scale, 20, 0.8304
-l3, normalised_english_counts, scale, 10, 0.5968
-l3, normalised_english_counts, scale, 5, 0.4114
-l3, scaled_english_counts, normalise, 300, 0.9994
-l3, scaled_english_counts, normalise, 100, 0.9984
-l3, scaled_english_counts, normalise, 50, 0.9876
-l3, scaled_english_counts, normalise, 30, 0.9284
-l3, scaled_english_counts, normalise, 20, 0.8322
-l3, scaled_english_counts, normalise, 10, 0.579
-l3, scaled_english_counts, normalise, 5, 0.3466
-l3, scaled_english_counts, scale, 300, 1.0
-l3, scaled_english_counts, scale, 100, 0.999
-l3, scaled_english_counts, scale, 50, 0.994
-l3, scaled_english_counts, scale, 30, 0.9688
-l3, scaled_english_counts, scale, 20, 0.8952
-l3, scaled_english_counts, scale, 10, 0.6416
-l3, scaled_english_counts, scale, 5, 0.4042
-cosine_distance, normalised_english_counts, normalise, 300, 0.9994
-cosine_distance, normalised_english_counts, normalise, 100, 1.0
-cosine_distance, normalised_english_counts, normalise, 50, 0.9978
-cosine_distance, normalised_english_counts, normalise, 30, 0.9856
-cosine_distance, normalised_english_counts, normalise, 20, 0.9374
-cosine_distance, normalised_english_counts, normalise, 10, 0.7212
-cosine_distance, normalised_english_counts, normalise, 5, 0.4282
-cosine_distance, normalised_english_counts, scale, 300, 0.9998
-cosine_distance, normalised_english_counts, scale, 100, 0.9994
-cosine_distance, normalised_english_counts, scale, 50, 0.9972
-cosine_distance, normalised_english_counts, scale, 30, 0.9846
-cosine_distance, normalised_english_counts, scale, 20, 0.9324
-cosine_distance, normalised_english_counts, scale, 10, 0.7144
-cosine_distance, normalised_english_counts, scale, 5, 0.4284
-cosine_distance, scaled_english_counts, normalise, 300, 0.9994
-cosine_distance, scaled_english_counts, normalise, 100, 0.9996
-cosine_distance, scaled_english_counts, normalise, 50, 0.9978
-cosine_distance, scaled_english_counts, normalise, 30, 0.9856
-cosine_distance, scaled_english_counts, normalise, 20, 0.935
-cosine_distance, scaled_english_counts, normalise, 10, 0.7232
-cosine_distance, scaled_english_counts, normalise, 5, 0.415
-cosine_distance, scaled_english_counts, scale, 300, 0.9982
-cosine_distance, scaled_english_counts, scale, 100, 0.9988
-cosine_distance, scaled_english_counts, scale, 50, 0.9976
-cosine_distance, scaled_english_counts, scale, 30, 0.9844
-cosine_distance, scaled_english_counts, scale, 20, 0.9314
-cosine_distance, scaled_english_counts, scale, 10, 0.7102
-cosine_distance, scaled_english_counts, scale, 5, 0.4376
-harmonic_mean, normalised_english_counts, normalise, 300, 0.4684
-harmonic_mean, normalised_english_counts, normalise, 100, 0.5068
-harmonic_mean, normalised_english_counts, normalise, 50, 0.6978
-harmonic_mean, normalised_english_counts, normalise, 30, 0.593
-harmonic_mean, normalised_english_counts, normalise, 20, 0.536
-harmonic_mean, normalised_english_counts, normalise, 10, 0.4284
-harmonic_mean, normalised_english_counts, normalise, 5, 0.3542
-harmonic_mean, normalised_english_counts, scale, 300, 0.3602
-harmonic_mean, normalised_english_counts, scale, 100, 0.57
-harmonic_mean, normalised_english_counts, scale, 50, 0.795
-harmonic_mean, normalised_english_counts, scale, 30, 0.7694
-harmonic_mean, normalised_english_counts, scale, 20, 0.6924
-harmonic_mean, normalised_english_counts, scale, 10, 0.559
-harmonic_mean, normalised_english_counts, scale, 5, 0.39
-harmonic_mean, scaled_english_counts, normalise, 300, 0.1214
-harmonic_mean, scaled_english_counts, normalise, 100, 0.132
-harmonic_mean, scaled_english_counts, normalise, 50, 0.1956
-harmonic_mean, scaled_english_counts, normalise, 30, 0.2686
-harmonic_mean, scaled_english_counts, normalise, 20, 0.258
-harmonic_mean, scaled_english_counts, normalise, 10, 0.2042
-harmonic_mean, scaled_english_counts, normalise, 5, 0.227
-harmonic_mean, scaled_english_counts, scale, 300, 0.7956
-harmonic_mean, scaled_english_counts, scale, 100, 0.5672
-harmonic_mean, scaled_english_counts, scale, 50, 0.4404
-harmonic_mean, scaled_english_counts, scale, 30, 0.3584
-harmonic_mean, scaled_english_counts, scale, 20, 0.3012
-harmonic_mean, scaled_english_counts, scale, 10, 0.2136
-harmonic_mean, scaled_english_counts, scale, 5, 0.1426
-geometric_mean, normalised_english_counts, normalise, 300, 0.9996
-geometric_mean, normalised_english_counts, normalise, 100, 0.9992
-geometric_mean, normalised_english_counts, normalise, 50, 0.9928
-geometric_mean, normalised_english_counts, normalise, 30, 0.9552
-geometric_mean, normalised_english_counts, normalise, 20, 0.8936
-geometric_mean, normalised_english_counts, normalise, 10, 0.6582
-geometric_mean, normalised_english_counts, normalise, 5, 0.4316
-geometric_mean, normalised_english_counts, scale, 300, 0.97
-geometric_mean, normalised_english_counts, scale, 100, 0.9762
-geometric_mean, normalised_english_counts, scale, 50, 0.9724
-geometric_mean, normalised_english_counts, scale, 30, 0.9224
-geometric_mean, normalised_english_counts, scale, 20, 0.8496
-geometric_mean, normalised_english_counts, scale, 10, 0.6846
-geometric_mean, normalised_english_counts, scale, 5, 0.4268
-geometric_mean, scaled_english_counts, normalise, 300, 0.9556
-geometric_mean, scaled_english_counts, normalise, 100, 0.8724
-geometric_mean, scaled_english_counts, normalise, 50, 0.7176
-geometric_mean, scaled_english_counts, normalise, 30, 0.6536
-geometric_mean, scaled_english_counts, normalise, 20, 0.5586
-geometric_mean, scaled_english_counts, normalise, 10, 0.3926
-geometric_mean, scaled_english_counts, normalise, 5, 0.319
-geometric_mean, scaled_english_counts, scale, 300, 0.7822
-geometric_mean, scaled_english_counts, scale, 100, 0.5784
-geometric_mean, scaled_english_counts, scale, 50, 0.4318
-geometric_mean, scaled_english_counts, scale, 30, 0.349
-geometric_mean, scaled_english_counts, scale, 20, 0.2932
-geometric_mean, scaled_english_counts, scale, 10, 0.2098
-geometric_mean, scaled_english_counts, scale, 5, 0.1406
+,message_length
+metric+scaling, 300,100,50,30,20,10,5
+l1:normalised, 0.9988, 0.9996, 0.9984, 0.9896, 0.953, 0.736, 0.44
+l1:euclidean_scaled, 0.9996, 1.0, 0.9988, 0.9896, 0.9518, 0.7536, 0.4418
+l1:normalised_with_identity, 0.9606, 0.9922, 0.988, 0.9644, 0.909, 0.7028, 0.4288
+l2:normalised, 0.9996, 0.9994, 0.9984, 0.981, 0.9302, 0.723, 0.4354
+l2:euclidean_scaled, 0.9992, 0.9992, 0.9984, 0.9836, 0.9298, 0.7116, 0.423
+l2:normalised_with_identity, 1.0, 0.9998, 0.9982, 0.986, 0.9322, 0.722, 0.4262
+l3:normalised, 0.9998, 0.999, 0.9952, 0.9536, 0.8742, 0.5964, 0.4078
+l3:euclidean_scaled, 0.9992, 0.9992, 0.9958, 0.9672, 0.8894, 0.6276, 0.4014
+l3:normalised_with_identity, 0.9998, 0.998, 0.97, 0.9002, 0.7686, 0.5484, 0.391
+cosine_distance:normalised, 0.999, 0.9994, 0.9984, 0.9854, 0.934, 0.7092, 0.4338
+cosine_distance:euclidean_scaled, 0.9996, 0.9992, 0.999, 0.9822, 0.9342, 0.7114, 0.4326
+cosine_distance:normalised_with_identity, 0.9994, 0.9994, 0.9984, 0.986, 0.9354, 0.7166, 0.4294
+harmonic_mean:normalised, 0.8154, 0.8382, 0.7618, 0.2696, 0.8678, 0.6736, 0.4566
+harmonic_mean:euclidean_scaled, 0.4756, 0.5108, 0.686, 0.6098, 0.5342, 0.4322, 0.3568
+harmonic_mean:normalised_with_identity, 0.9574, 0.969, 0.952, 0.9254, 0.897, 0.7368, 0.4434
+geometric_mean:normalised, 0.9996, 0.9996, 0.9914, 0.9178, 0.9368, 0.7114, 0.4562
+geometric_mean:euclidean_scaled, 0.9998, 0.999, 0.9962, 0.9534, 0.8824, 0.6548, 0.443
+geometric_mean:normalised_with_identity, 0.9426, 0.9872, 0.9848, 0.9694, 0.9358, 0.7654, 0.4582
+inverse_log_pl:normalised, 0.9994, 0.9996, 0.9992, 0.996, 0.98, 0.8088, 0.488
+inverse_log_pl:euclidean_scaled, 0.9998, 0.9998, 0.9996, 0.996, 0.9826, 0.817, 0.481
+inverse_log_pl:normalised_with_identity, 0.999, 0.9996, 0.9992, 0.9978, 0.9802, 0.8106, 0.483