StockPrediction/plots/data/MLP_50_20.csv

1	time_window	training_accuracy	testing_accuracy
2	1	0.5366158981848529	0.5217028380634391
3	2	0.5899415692821369	0.5350584307178631
4	3	0.6750834724540902	0.5087719298245614
5	4	0.7261532039240242	0.48120300751879697
6	5	0.7701461377870563	0.49958228905597324
7	6	0.7584046773856755	0.5087719298245614
8	7	0.7644110275689223	0.5430242272347535
9	8	0.8398078529657477	0.49414715719063546
10	9	0.8748694380614164	0.5016722408026756
11	10	0.9352277475971584	0.47240802675585286
12	11	0.9264367816091954	0.4807692307692308
13	12	0.9423076923076923	0.520066889632107
14	13	0.9412625418060201	0.4794979079497908
15	14	0.9272423165377378	0.507949790794979
16	15	0.958594730238394	0.5196652719665272
17	16	0.9811754862999372	0.497071129707113
18	17	0.992887029288703	0.5263598326359833
19	18	0.9947698744769874	0.509212730318258
20	19	0.9922577945176815	0.49581239530988275
21	20	0.9945583926329008	0.525963149078727
22	21	0.9920452166631777	0.509212730318258
23	22	0.9972780569514238	0.5117252931323283
24	23	0.9886934673366834	0.49958088851634536
25	24	0.9912041884816754	0.5046102263202011
26	25	0.9981147884373691	0.509639564124057
27	26	0.9974858579509742	0.5004191114836547
28	27	0.9945515507124896	0.5297569153394803
29	28	1.0	0.5033557046979866
30	29	0.9997904003353595	0.5260067114093959
31	30	0.99958071278826	0.5243288590604027
32	31	1.0	0.47818791946308725
33	32	1.0	0.5151006711409396
34	33	0.9991610738255033	0.5264483627204031
35	34	1.0	0.4979009235936188
36	35	0.9987410826689047	0.5029387069689337
37	36	1.0	0.5188916876574308
38	37	1.0	0.4869857262804366
39	38	1.0	0.49411764705882355
40	39	1.0	0.5117647058823529
41	40	1.0	0.5243697478991597
42	41	1.0	0.5184873949579832
43	42	0.9997899159663866	0.49747899159663866
44	43	1.0	0.5063078216989066
45	44	1.0	0.48107653490328006
46	45	1.0	0.4920100925147183
47	46	1.0	0.5088309503784693
48	47	0.9997897392767031	0.4953742640874685
49	48	1.0	0.515993265993266
50	49	1.0	0.4772727272727273
51	50	1.0	0.5067340067340067