Optimize code performance

Example.py

@@ -21,21 +21,23 @@
 
 
 # for reproducibility
-np.random.seed(20170925)
+np.random.seed(20240919)
 
-m.fit_scores(balance=True, nmodels=10,n_jobs=3,model_type='tree')
+m.fit_scores(balance=True, nmodels=10,n_jobs=3,model_type='linear')
+# m.fit_scores(balance=True, nmodels=10,n_jobs=3,model_type='tree')
 
 
 m.predict_scores()
 
 m.plot_scores()
 m.tune_threshold(method='random')
-m.match(method="min", nmatches=1, threshold=0.0005)
+m.match(method="min", nmatches=1, threshold=0.0001)
 
 m.record_frequency()
 m.assign_weight_vector()
-m.matched_data.sort_values("match_id").head(6)
-categorical_results = m.compare_categorical(return_table=True)
+print("top 6 matched data")
+print(m.matched_data.sort_values("match_id").head(6))
+categorical_results = m.compare_categorical(return_table=True,plot_result=True)
 print(categorical_results)
-cc = m.compare_continuous(return_table=True)
+cc = m.compare_continuous(return_table=True,plot_result=True)
 print(cc)

catboost_info/learn_error.tsv

@@ -1,101 +1,101 @@
 iter	Logloss
-0	0.6860339355
-1	0.6793117676
-2	0.6719605103
-3	0.6662591553
-4	0.6604979248
-5	0.6564853516
-6	0.6521936035
-7	0.6470774536
-8	0.6438172607
-9	0.6417221069
-10	0.638303833
-11	0.6358477783
-12	0.6319497681
-13	0.629239502
-14	0.6270506592
-15	0.6237658691
-16	0.622847229
-17	0.6217990723
-18	0.6188481445
-19	0.617229126
-20	0.615310791
-21	0.6141380005
-22	0.612633667
-23	0.6099338379
-24	0.6079963989
-25	0.6060895386
-26	0.6051459961
-27	0.6039931641
-28	0.6024761963
-29	0.6013486328
-30	0.6000162354
-31	0.5989101562
-32	0.5965554199
-33	0.5950981445
-34	0.5945324707
-35	0.5931483154
-36	0.5912705078
-37	0.5901569824
-38	0.5892490234
-39	0.5883467407
-40	0.5871303711
-41	0.5852086182
-42	0.5846987305
-43	0.5836748657
-44	0.5832843018
-45	0.5825790405
-46	0.581152832
-47	0.579135376
-48	0.5781837158
-49	0.5773459473
-50	0.576769104
-51	0.5762745361
-52	0.5759954834
-53	0.5753961792
-54	0.5739927368
-55	0.5722527466
-56	0.5716566162
-57	0.5711035156
-58	0.5702729492
-59	0.5696401367
-60	0.5691248169
-61	0.56871698
-62	0.5680968018
-63	0.5676867676
-64	0.5665188599
-65	0.5655626221
-66	0.5643121948
-67	0.5639257202
-68	0.5630357666
-69	0.5618366699
-70	0.5606151123
-71	0.5599468994
-72	0.5588881836
-73	0.5577629395
-74	0.5568980103
-75	0.556286499
-76	0.5554761963
-77	0.5545211182
-78	0.5535883179
-79	0.5530195923
-80	0.5520428467
-81	0.5517469482
-82	0.5512855835
-83	0.550744873
-84	0.5501694946
-85	0.5498062744
-86	0.5494074097
-87	0.5484682617
-88	0.5480986938
-89	0.5477758789
-90	0.5471382446
-91	0.5454927368
-92	0.5450218506
-93	0.5444959717
-94	0.5438290405
-95	0.5432046509
-96	0.5414328613
-97	0.5410144653
-98	0.5401860962
-99	0.5391330566
+0	0.6898436129
+1	0.6866067364
+2	0.68367803
+3	0.6810237609
+4	0.678237323
+5	0.6754873811
+6	0.6725127503
+7	0.6696807072
+8	0.6670089812
+9	0.6646403495
+10	0.6624498627
+11	0.6601588291
+12	0.6578551217
+13	0.6560402765
+14	0.6543410543
+15	0.65227048
+16	0.6503630072
+17	0.6480629463
+18	0.6462505614
+19	0.6447754391
+20	0.6432293827
+21	0.6415947907
+22	0.6397645899
+23	0.6382946974
+24	0.6368448744
+25	0.6356910387
+26	0.6341236671
+27	0.6325919069
+28	0.6312917997
+29	0.6299907921
+30	0.6287321632
+31	0.6276005753
+32	0.6261165329
+33	0.6248845573
+34	0.6238661652
+35	0.6229098852
+36	0.6216585476
+37	0.6200600856
+38	0.6190215175
+39	0.6176280993
+40	0.6165708879
+41	0.6154169445
+42	0.6144099411
+43	0.6136239551
+44	0.6127241017
+45	0.6115466937
+46	0.6108540474
+47	0.6099583288
+48	0.6089160687
+49	0.6080244778
+50	0.6072035247
+51	0.6063910223
+52	0.6054369286
+53	0.6046599699
+54	0.6036734044
+55	0.6028371936
+56	0.6020923298
+57	0.6014557316
+58	0.6004762273
+59	0.5997872878
+60	0.599063142
+61	0.5978535788
+62	0.5971596732
+63	0.5965502677
+64	0.5958384615
+65	0.5950384992
+66	0.5943805379
+67	0.5934463087
+68	0.5927613174
+69	0.5919319031
+70	0.5911521936
+71	0.5905110816
+72	0.5900454666
+73	0.5893650325
+74	0.5888609676
+75	0.58810042
+76	0.5873504981
+77	0.5867293906
+78	0.5863017951
+79	0.5856087136
+80	0.584768032
+81	0.5843725607
+82	0.5838055977
+83	0.583500797
+84	0.5827138536
+85	0.5821745753
+86	0.581087886
+87	0.5807264777
+88	0.5801221541
+89	0.5797372208
+90	0.5789359288
+91	0.5782544419
+92	0.5778428999
+93	0.5772284707
+94	0.576600707
+95	0.5761930174
+96	0.5758104707
+97	0.5754176143
+98	0.5747088356
+99	0.5742526543