Tweaks, and record of a run
[cipher-tools.git] / caesar_break_parameter_trials.csv
index df9b836ebdfec843d0f42cb319729dfd1a45836c..37e60fb26903064644413deaa65da8d7d8b91102 100644 (file)
-l1, normalised_english_counts, normalise, 3000, 0.9616
-l1, normalised_english_counts, normalise, 1000, 0.9562
-l1, normalised_english_counts, normalise, 300, 0.9598
-l1, normalised_english_counts, normalise, 100, 0.9622
-l1, normalised_english_counts, normalise, 50, 0.9584
-l1, normalised_english_counts, normalise, 30, 0.953
-l1, normalised_english_counts, normalise, 20, 0.917
-l1, normalised_english_counts, normalise, 10, 0.7328
-l1, normalised_english_counts, normalise, 5, 0.4394
-l1, normalised_english_counts, scale, 3000, 0.9618
-l1, normalised_english_counts, scale, 1000, 0.9574
-l1, normalised_english_counts, scale, 300, 0.9624
-l1, normalised_english_counts, scale, 100, 0.9566
-l1, normalised_english_counts, scale, 50, 0.959
-l1, normalised_english_counts, scale, 30, 0.9476
-l1, normalised_english_counts, scale, 20, 0.8968
-l1, normalised_english_counts, scale, 10, 0.6844
-l1, normalised_english_counts, scale, 5, 0.4298
-l1, scaled_english_counts, normalise, 3000, 0.957
-l1, scaled_english_counts, normalise, 1000, 0.9662
-l1, scaled_english_counts, normalise, 300, 0.9604
-l1, scaled_english_counts, normalise, 100, 0.9602
-l1, scaled_english_counts, normalise, 50, 0.9578
-l1, scaled_english_counts, normalise, 30, 0.9504
-l1, scaled_english_counts, normalise, 20, 0.9174
-l1, scaled_english_counts, normalise, 10, 0.7204
-l1, scaled_english_counts, normalise, 5, 0.4506
-l1, scaled_english_counts, scale, 3000, 0.9584
-l1, scaled_english_counts, scale, 1000, 0.9586
-l1, scaled_english_counts, scale, 300, 0.964
-l1, scaled_english_counts, scale, 100, 0.9582
-l1, scaled_english_counts, scale, 50, 0.9606
-l1, scaled_english_counts, scale, 30, 0.944
-l1, scaled_english_counts, scale, 20, 0.915
-l1, scaled_english_counts, scale, 10, 0.7324
-l1, scaled_english_counts, scale, 5, 0.4446
-l2, normalised_english_counts, normalise, 3000, 0.953
-l2, normalised_english_counts, normalise, 1000, 0.962
-l2, normalised_english_counts, normalise, 300, 0.9638
-l2, normalised_english_counts, normalise, 100, 0.9632
-l2, normalised_english_counts, normalise, 50, 0.9604
-l2, normalised_english_counts, normalise, 30, 0.95
-l2, normalised_english_counts, normalise, 20, 0.892
-l2, normalised_english_counts, normalise, 10, 0.7124
-l2, normalised_english_counts, normalise, 5, 0.4406
-l2, normalised_english_counts, scale, 3000, 0.9626
-l2, normalised_english_counts, scale, 1000, 0.956
-l2, normalised_english_counts, scale, 300, 0.962
-l2, normalised_english_counts, scale, 100, 0.9572
-l2, normalised_english_counts, scale, 50, 0.9526
-l2, normalised_english_counts, scale, 30, 0.9478
-l2, normalised_english_counts, scale, 20, 0.9046
-l2, normalised_english_counts, scale, 10, 0.6896
-l2, normalised_english_counts, scale, 5, 0.4308
-l2, scaled_english_counts, normalise, 3000, 0.9574
-l2, scaled_english_counts, normalise, 1000, 0.9568
-l2, scaled_english_counts, normalise, 300, 0.9536
-l2, scaled_english_counts, normalise, 100, 0.9624
-l2, scaled_english_counts, normalise, 50, 0.9606
-l2, scaled_english_counts, normalise, 30, 0.9384
-l2, scaled_english_counts, normalise, 20, 0.8914
-l2, scaled_english_counts, normalise, 10, 0.6892
-l2, scaled_english_counts, normalise, 5, 0.4196
-l2, scaled_english_counts, scale, 3000, 0.9532
-l2, scaled_english_counts, scale, 1000, 0.9588
-l2, scaled_english_counts, scale, 300, 0.9644
-l2, scaled_english_counts, scale, 100, 0.9572
-l2, scaled_english_counts, scale, 50, 0.9586
-l2, scaled_english_counts, scale, 30, 0.9436
-l2, scaled_english_counts, scale, 20, 0.9036
-l2, scaled_english_counts, scale, 10, 0.693
-l2, scaled_english_counts, scale, 5, 0.4376
-l3, normalised_english_counts, normalise, 3000, 0.9626
-l3, normalised_english_counts, normalise, 1000, 0.9582
-l3, normalised_english_counts, normalise, 300, 0.9542
-l3, normalised_english_counts, normalise, 100, 0.9606
-l3, normalised_english_counts, normalise, 50, 0.953
-l3, normalised_english_counts, normalise, 30, 0.9248
-l3, normalised_english_counts, normalise, 20, 0.8684
-l3, normalised_english_counts, normalise, 10, 0.6106
-l3, normalised_english_counts, normalise, 5, 0.4064
-l3, normalised_english_counts, scale, 3000, 0.961
-l3, normalised_english_counts, scale, 1000, 0.9568
-l3, normalised_english_counts, scale, 300, 0.9566
-l3, normalised_english_counts, scale, 100, 0.9554
-l3, normalised_english_counts, scale, 50, 0.9436
-l3, normalised_english_counts, scale, 30, 0.8936
-l3, normalised_english_counts, scale, 20, 0.8016
-l3, normalised_english_counts, scale, 10, 0.579
-l3, normalised_english_counts, scale, 5, 0.4114
-l3, scaled_english_counts, normalise, 3000, 0.9616
-l3, scaled_english_counts, normalise, 1000, 0.9612
-l3, scaled_english_counts, normalise, 300, 0.9624
-l3, scaled_english_counts, normalise, 100, 0.9524
-l3, scaled_english_counts, normalise, 50, 0.9474
-l3, scaled_english_counts, normalise, 30, 0.9066
-l3, scaled_english_counts, normalise, 20, 0.8004
-l3, scaled_english_counts, normalise, 10, 0.5686
-l3, scaled_english_counts, normalise, 5, 0.3404
-l3, scaled_english_counts, scale, 3000, 0.96
-l3, scaled_english_counts, scale, 1000, 0.96
-l3, scaled_english_counts, scale, 300, 0.9596
-l3, scaled_english_counts, scale, 100, 0.96
-l3, scaled_english_counts, scale, 50, 0.954
-l3, scaled_english_counts, scale, 30, 0.9374
-l3, scaled_english_counts, scale, 20, 0.862
-l3, scaled_english_counts, scale, 10, 0.6276
-l3, scaled_english_counts, scale, 5, 0.399
-cosine_distance, normalised_english_counts, normalise, 3000, 0.9618
-cosine_distance, normalised_english_counts, normalise, 1000, 0.96
-cosine_distance, normalised_english_counts, normalise, 300, 0.9604
-cosine_distance, normalised_english_counts, normalise, 100, 0.9538
-cosine_distance, normalised_english_counts, normalise, 50, 0.9608
-cosine_distance, normalised_english_counts, normalise, 30, 0.9426
-cosine_distance, normalised_english_counts, normalise, 20, 0.9012
-cosine_distance, normalised_english_counts, normalise, 10, 0.6916
-cosine_distance, normalised_english_counts, normalise, 5, 0.4286
-cosine_distance, normalised_english_counts, scale, 3000, 0.9606
-cosine_distance, normalised_english_counts, scale, 1000, 0.9572
-cosine_distance, normalised_english_counts, scale, 300, 0.9628
-cosine_distance, normalised_english_counts, scale, 100, 0.959
-cosine_distance, normalised_english_counts, scale, 50, 0.9542
-cosine_distance, normalised_english_counts, scale, 30, 0.951
-cosine_distance, normalised_english_counts, scale, 20, 0.9028
-cosine_distance, normalised_english_counts, scale, 10, 0.7028
-cosine_distance, normalised_english_counts, scale, 5, 0.44
-cosine_distance, scaled_english_counts, normalise, 3000, 0.9582
-cosine_distance, scaled_english_counts, normalise, 1000, 0.9614
-cosine_distance, scaled_english_counts, normalise, 300, 0.9632
-cosine_distance, scaled_english_counts, normalise, 100, 0.9584
-cosine_distance, scaled_english_counts, normalise, 50, 0.9574
-cosine_distance, scaled_english_counts, normalise, 30, 0.9506
-cosine_distance, scaled_english_counts, normalise, 20, 0.8956
-cosine_distance, scaled_english_counts, normalise, 10, 0.6916
-cosine_distance, scaled_english_counts, normalise, 5, 0.4356
-cosine_distance, scaled_english_counts, scale, 3000, 0.9572
-cosine_distance, scaled_english_counts, scale, 1000, 0.961
-cosine_distance, scaled_english_counts, scale, 300, 0.9596
-cosine_distance, scaled_english_counts, scale, 100, 0.9544
-cosine_distance, scaled_english_counts, scale, 50, 0.9598
-cosine_distance, scaled_english_counts, scale, 30, 0.9414
-cosine_distance, scaled_english_counts, scale, 20, 0.9036
-cosine_distance, scaled_english_counts, scale, 10, 0.6928
-cosine_distance, scaled_english_counts, scale, 5, 0.4178
+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
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+'l2', 'normalised', 10,1.2958
+'geometric_mean', 'normalised_with_identity', 5,0.464
+'l1', 'normalised_with_identity', 30,0.9562
+'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
+'inverse_log_pl', 'normalised', 30,0.995
+'l1', 'normalised', 30,0.9916
+'l2', 'normalised_with_identity', 300,1.9984
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+'geometric_mean', 'euclidean_scaled', 50,0.9938
+'cosine_distance', 'euclidean_scaled', 10,0.7118
+'harmonic_mean', 'normalised', 50,0.7522
+'l1', 'normalised_with_identity', 50,0.9884
+'inverse_log_pl', 'normalised_with_identity', 30,0.9964
+'harmonic_mean', 'normalised', 30,0.2622
+'geometric_mean', 'normalised', 300,0.9986
+'inverse_log_pl', 'normalised_with_identity', 50,0.9994
+'inverse_log_pl', 'euclidean_scaled', 100,0.9998
+'cosine_distance', 'normalised', 10,0.7008
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+'l1', 'euclidean_scaled', 30,0.9896
+'inverse_log_pl', 'euclidean_scaled', 300,0.9994
+'inverse_log_pl', 'normalised_with_identity', 10,0.8118
+'geometric_mean', 'normalised', 50,0.9902
+'l1', 'euclidean_scaled', 50,0.9984
+'l2', 'normalised_with_identity', 5,0.8336
+'geometric_mean', 'normalised', 5,0.4578
+'l2', 'normalised', 50,1.9936
+'harmonic_mean', 'normalised_with_identity', 50,0.9532
+'cosine_distance', 'euclidean_scaled', 5,0.4254
+'geometric_mean', 'normalised', 20,0.9404
+'cosine_distance', 'normalised_with_identity', 10,0.7152
+'geometric_mean', 'normalised_with_identity', 30,0.9718
+'cosine_distance', 'euclidean_scaled', 30,0.9826
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+'l2', 'euclidean_scaled', 50,1.9918
+'l2', 'euclidean_scaled', 5,0.8332
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+'cosine_distance', 'normalised_with_identity', 300,0.9994
+'inverse_log_pl', 'normalised', 300,0.9996
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+'geometric_mean', 'normalised', 30,0.9208
+'cosine_distance', 'normalised_with_identity', 20,0.9368
+'cosine_distance', 'normalised', 100,0.9994
+'geometric_mean', 'normalised_with_identity', 20,0.9394
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+'geometric_mean', 'normalised_with_identity', 50,0.989
+'l2', 'normalised', 100,1.9992
+'cosine_distance', 'euclidean_scaled', 50,0.998
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+'harmonic_mean', 'normalised_with_identity', 300,0.9526
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+'cosine_distance', 'normalised', 30,0.9816
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+'harmonic_mean', 'normalised', 10,0.6732
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+'l1', 'euclidean_scaled', 300,0.9996
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+'l1', 'euclidean_scaled', 100,1.0
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+'l1', 'normalised', 10,0.7374
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