You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

13.csv 3.3 kB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364
  1. 2.000000000000000000e+01,2.600000000000000000e+01
  2. 1.180000000000000000e+02,-5.800000000000000000e+01
  3. 2.450000000000000000e+02,-1.660000000000000000e+02
  4. 1.600000000000000000e+02,-3.900000000000000000e+01
  5. 1.580000000000000000e+02,7.000000000000000000e+01
  6. 3.000000000000000000e+01,6.200000000000000000e+01
  7. -9.800000000000000000e+01,1.360000000000000000e+02
  8. -1.000000000000000000e+02,2.060000000000000000e+02
  9. -7.800000000000000000e+01,2.580000000000000000e+02
  10. -1.220000000000000000e+02,3.460000000000000000e+02
  11. -1.020000000000000000e+02,2.740000000000000000e+02
  12. -1.160000000000000000e+02,1.460000000000000000e+02
  13. -1.460000000000000000e+02,1.800000000000000000e+01
  14. -1.780000000000000000e+02,-6.000000000000000000e+00
  15. -1.900000000000000000e+02,-1.400000000000000000e+01
  16. -1.780000000000000000e+02,-2.400000000000000000e+01
  17. -1.940000000000000000e+02,-1.400000000000000000e+01
  18. -1.880000000000000000e+02,-2.200000000000000000e+01
  19. -2.240000000000000000e+02,-3.000000000000000000e+01
  20. -2.020000000000000000e+02,-3.400000000000000000e+01
  21. -2.280000000000000000e+02,-4.400000000000000000e+01
  22. -2.440000000000000000e+02,-3.000000000000000000e+01
  23. -2.680000000000000000e+02,-5.800000000000000000e+01
  24. -2.600000000000000000e+02,-6.000000000000000000e+01
  25. -3.080000000000000000e+02,-7.000000000000000000e+01
  26. -3.040000000000000000e+02,-6.800000000000000000e+01
  27. -2.860000000000000000e+02,-8.200000000000000000e+01
  28. -2.700000000000000000e+02,-8.000000000000000000e+01
  29. -2.600000000000000000e+02,-9.600000000000000000e+01
  30. -2.460000000000000000e+02,-1.000000000000000000e+02
  31. -2.180000000000000000e+02,-9.400000000000000000e+01
  32. -1.900000000000000000e+02,-1.100000000000000000e+02
  33. -1.240000000000000000e+02,-1.140000000000000000e+02
  34. -1.600000000000000000e+02,-8.600000000000000000e+01
  35. -7.600000000000000000e+01,-7.600000000000000000e+01
  36. -8.000000000000000000e+00,-7.000000000000000000e+01
  37. -4.200000000000000000e+01,-5.000000000000000000e+01
  38. 3.400000000000000000e+01,-4.000000000000000000e+01
  39. 4.000000000000000000e+00,-2.600000000000000000e+01
  40. 3.400000000000000000e+01,-2.800000000000000000e+01
  41. 2.200000000000000000e+01,-1.200000000000000000e+01
  42. 6.000000000000000000e+01,-6.000000000000000000e+00
  43. -4.000000000000000000e+00,2.000000000000000000e+00
  44. 3.400000000000000000e+01,6.000000000000000000e+00
  45. 4.800000000000000000e+01,1.000000000000000000e+01
  46. 3.400000000000000000e+01,1.200000000000000000e+01
  47. 4.200000000000000000e+01,1.800000000000000000e+01
  48. 5.200000000000000000e+01,2.200000000000000000e+01
  49. 5.200000000000000000e+01,2.000000000000000000e+01
  50. 7.800000000000000000e+01,1.400000000000000000e+01
  51. 7.200000000000000000e+01,3.000000000000000000e+01
  52. 1.360000000000000000e+02,4.600000000000000000e+01
  53. 1.100000000000000000e+02,6.200000000000000000e+01
  54. 1.420000000000000000e+02,6.200000000000000000e+01
  55. 1.520000000000000000e+02,5.400000000000000000e+01
  56. 1.960000000000000000e+02,1.800000000000000000e+01
  57. 1.620000000000000000e+02,-1.600000000000000000e+01
  58. 4.400000000000000000e+01,-4.000000000000000000e+00
  59. 1.710000000000000000e+02,-1.400000000000000000e+01
  60. 9.000000000000000000e+01,-1.800000000000000000e+01
  61. 5.000000000000000000e+01,-3.000000000000000000e+01
  62. -7.800000000000000000e+01,-9.000000000000000000e+01
  63. -2.060000000000000000e+02,-2.180000000000000000e+02
  64. -3.340000000000000000e+02,-3.460000000000000000e+02

全栈的自动化机器学习系统,主要针对多变量时间序列数据的异常检测。TODS提供了详尽的用于构建基于机器学习的异常检测系统的模块,它们包括:数据处理(data processing),时间序列处理( time series processing),特征分析(feature analysis),检测算法(detection algorithms),和强化模块( reinforcement module)。这些模块所提供的功能包括常见的数据预处理、时间序列数据的平滑或变换,从时域或频域中抽取特征、多种多样的检测算