Tweaks, and record of a run

[cipher-tools.git] / caesar_break_parameter_trials.csv

diff --git a/caesar_break_parameter_trials.csv b/caesar_break_parameter_trials.csv
index ba7ee273a0682301beab9d4da6d0db1cba45f0ec..37e60fb26903064644413deaa65da8d7d8b91102 100644 (file)
--- a/caesar_break_parameter_trials.csv
+++ b/caesar_break_parameter_trials.csv
@@ -1,168 +1,127 @@
-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
+metric,scaling,message_length,score
+'l2', 'normalised_with_identity', 50,1.969
+'l2', 'euclidean_scaled', 10,1.3528
+'l2', 'euclidean_scaled', 100,1.998
+'inverse_log_pl', 'normalised_with_identity', 100,0.9994
+'l1', 'normalised', 100,1.0
+'inverse_log_pl', 'normalised', 20,0.9814
+'l2', 'normalised_with_identity', 20,1.7306
+'l2', 'euclidean_scaled', 300,1.9984
+'cosine_distance', 'normalised', 5,0.4382
+'l2', 'normalised', 5,0.8352
+'l1', 'normalised', 300,0.9998
+'cosine_distance', 'normalised', 50,0.9968
+'inverse_log_pl', 'normalised', 5,0.4866
+'harmonic_mean', 'normalised', 5,0.4616
+'l2', 'normalised_with_identity', 10,1.2578
+'geometric_mean', 'normalised', 10,0.726
+'harmonic_mean', 'normalised_with_identity', 10,0.7482
+'harmonic_mean', 'euclidean_scaled', 50,0.6858
+'inverse_log_pl', 'normalised', 10,0.813
+'l1', 'normalised_with_identity', 5,0.4436
+'inverse_log_pl', 'euclidean_scaled', 50,0.9996
+'inverse_log_pl', 'normalised', 50,0.9992
+'l1', 'euclidean_scaled', 20,0.9532
+'geometric_mean', 'normalised_with_identity', 10,0.7706
+'l2', 'normalised', 300,1.9992
+'l1', 'normalised', 5,0.4384
+'cosine_distance', 'normalised_with_identity', 5,0.4398
+'l1', 'normalised_with_identity', 300,0.9578
+'inverse_log_pl', 'normalised_with_identity', 20,0.9826
+'inverse_log_pl', 'euclidean_scaled', 20,0.9786
+'harmonic_mean', 'normalised', 100,0.8316
+'l2', 'normalised', 10,1.2958
+'geometric_mean', 'normalised_with_identity', 5,0.464
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+'cosine_distance', 'normalised', 20,0.9338
+'l1', 'normalised_with_identity', 10,0.7094
+'harmonic_mean', 'normalised_with_identity', 5,0.4542
+'geometric_mean', 'euclidean_scaled', 100,0.9992
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+'l1', 'normalised', 30,0.9916
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+'l2', 'euclidean_scaled', 30,1.9528
+'geometric_mean', 'euclidean_scaled', 50,0.9938
+'cosine_distance', 'euclidean_scaled', 10,0.7118
+'harmonic_mean', 'normalised', 50,0.7522
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+'geometric_mean', 'normalised', 50,0.9902
+'l1', 'euclidean_scaled', 50,0.9984
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+'l2', 'normalised', 50,1.9936
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+'cosine_distance', 'euclidean_scaled', 5,0.4254
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+'geometric_mean', 'normalised_with_identity', 30,0.9718
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