-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
+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
projects / cipher-tools.git / blobdiff