crypto_predictor
1bd9d25f60
- 删除测试脚本: test_2026_classification.py, test_lagllama.py, test_timesfm.py, test_ttm.py - 删除2019相关文件: analyze_2019_*, apply_2019_*, dlinear_2019_*, three_models_2019_* - 添加集成模型相关代码和分析脚本 - 添加N-BEATS模型和CatBoost分类模型
142 lines
4.0 KiB
Plaintext
142 lines
4.0 KiB
Plaintext
iter Accuracy Logloss
|
|
0 0.5470774019 0.6925856518
|
|
1 0.5485192475 0.6920296194
|
|
2 0.5508078912 0.6915437145
|
|
3 0.5511969607 0.6911042525
|
|
4 0.5528218977 0.6906429178
|
|
5 0.553096535 0.6902328044
|
|
6 0.5537144688 0.6899070645
|
|
7 0.552730352 0.6895966245
|
|
8 0.5539204467 0.6892625204
|
|
9 0.554561267 0.6889386437
|
|
10 0.554561267 0.6886345552
|
|
11 0.5548587907 0.6883728473
|
|
12 0.5552020872 0.6881185803
|
|
13 0.5564150684 0.6879043975
|
|
14 0.5559802261 0.6877314929
|
|
15 0.5564150684 0.6875118582
|
|
16 0.5569414565 0.6872755986
|
|
17 0.5561862041 0.6870435386
|
|
18 0.5561633176 0.6868442431
|
|
19 0.5575593903 0.6866694237
|
|
20 0.5575593903 0.686503203
|
|
21 0.557124548 0.6863452751
|
|
22 0.5569185701 0.6862172686
|
|
23 0.5573762988 0.6860730724
|
|
24 0.5571703209 0.6859302623
|
|
25 0.5570101158 0.6858087212
|
|
26 0.5571474344 0.6857036471
|
|
27 0.5571932073 0.6855803136
|
|
28 0.5572160937 0.6854590307
|
|
29 0.5568041379 0.6853245403
|
|
30 0.5570558887 0.6852010211
|
|
31 0.5570330022 0.6850648161
|
|
32 0.5578340276 0.6849486439
|
|
33 0.5576738225 0.6848167763
|
|
34 0.5577424818 0.6847064338
|
|
35 0.5582917563 0.6846073419
|
|
36 0.5587037122 0.6845016816
|
|
37 0.5587494851 0.6844106082
|
|
38 0.5591156681 0.6843432648
|
|
39 0.5589325766 0.6842678359
|
|
40 0.5590012359 0.6841515192
|
|
41 0.5590698952 0.6840610381
|
|
42 0.5593445324 0.6839565281
|
|
43 0.5592529867 0.6838539206
|
|
44 0.559321646 0.6837417759
|
|
45 0.559687829 0.6836669298
|
|
46 0.5603744221 0.6835634424
|
|
47 0.5599853527 0.6834698484
|
|
48 0.5601913306 0.6833860083
|
|
49 0.5602599899 0.6833086288
|
|
50 0.5606490594 0.683239475
|
|
51 0.5609694695 0.6831625258
|
|
52 0.5611983339 0.683056699
|
|
53 0.5617018355 0.6829611591
|
|
54 0.5619993592 0.6828690012
|
|
55 0.5620451321 0.6827776665
|
|
56 0.5624342015 0.6826927644
|
|
57 0.5626401794 0.6825957686
|
|
58 0.5626630659 0.6825449467
|
|
59 0.5627088387 0.6824559998
|
|
60 0.562983476 0.6823684725
|
|
61 0.5632352268 0.6822923813
|
|
62 0.5630521353 0.6822333406
|
|
63 0.5634412047 0.6821367311
|
|
64 0.5636242962 0.6820867227
|
|
65 0.563715842 0.6820256999
|
|
66 0.5638531606 0.6819329129
|
|
67 0.5638989335 0.6818706983
|
|
68 0.5639447064 0.6818045601
|
|
69 0.564082025 0.68171304
|
|
70 0.5640362521 0.6816251881
|
|
71 0.5645168673 0.6815203712
|
|
72 0.564448208 0.6814559429
|
|
73 0.5646541859 0.6813334168
|
|
74 0.5649059367 0.6812138418
|
|
75 0.5649059367 0.6811428702
|
|
76 0.565180574 0.6810679335
|
|
77 0.5653407791 0.6810189357
|
|
78 0.5655696434 0.6809239905
|
|
79 0.5651119147 0.6808452293
|
|
80 0.5653407791 0.6807843648
|
|
81 0.565180574 0.6807084812
|
|
82 0.5654780977 0.6806237044
|
|
83 0.5656840756 0.680541791
|
|
84 0.5653636655 0.6804402561
|
|
85 0.565546757 0.6803841011
|
|
86 0.5657298485 0.6803302076
|
|
87 0.5663248959 0.6802294187
|
|
88 0.5660273722 0.6801427052
|
|
89 0.5664393281 0.680092343
|
|
90 0.5666224196 0.6800188515
|
|
91 0.567377672 0.6799633931
|
|
92 0.5676523092 0.6799142593
|
|
93 0.5677667414 0.6798218244
|
|
94 0.5679727194 0.6797624264
|
|
95 0.5682702431 0.6796825487
|
|
96 0.5683160159 0.6796119175
|
|
97 0.5681786973 0.6795251979
|
|
98 0.5684533346 0.6794647206
|
|
99 0.5690026091 0.6793963783
|
|
100 0.5689797226 0.6793126045
|
|
101 0.569208587 0.6792105367
|
|
102 0.5693687921 0.6791494493
|
|
103 0.5695518836 0.6790732211
|
|
104 0.5698265208 0.6789905315
|
|
105 0.5698951801 0.67895488
|
|
106 0.5700324987 0.6788948137
|
|
107 0.5704902275 0.6788457101
|
|
108 0.5704902275 0.6787737664
|
|
109 0.5708106376 0.6786897689
|
|
110 0.5709021834 0.6786357569
|
|
111 0.5711768206 0.6785404316
|
|
112 0.5714972307 0.6784635222
|
|
113 0.5716345494 0.6783830081
|
|
114 0.5716803222 0.6783261377
|
|
115 0.5717947544 0.6782551829
|
|
116 0.5717260951 0.6782039946
|
|
117 0.5719549595 0.6781381441
|
|
118 0.5720007324 0.6780959678
|
|
119 0.5721609374 0.6780580972
|
|
120 0.5722982561 0.6779909469
|
|
121 0.5722753696 0.6779155506
|
|
122 0.5726186662 0.67787157
|
|
123 0.5729161899 0.6778021605
|
|
124 0.5732594864 0.6777441308
|
|
125 0.5737172152 0.6776640278
|
|
126 0.5741062846 0.6775768826
|
|
127 0.5738545338 0.6775322572
|
|
128 0.5738545338 0.6774381457
|
|
129 0.5739460796 0.6773933791
|
|
130 0.5738545338 0.6773073305
|
|
131 0.5746555591 0.6772430348
|
|
132 0.5745640134 0.6771630132
|
|
133 0.5747242184 0.6770868641
|
|
134 0.5749988557 0.6770144627
|
|
135 0.5747699913 0.6769488704
|
|
136 0.5751590607 0.6768712881
|
|
137 0.5755939031 0.6767999464
|
|
138 0.5755710166 0.6767315844
|
|
139 0.5758914267 0.6766580612
|