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.

174.csv 5.0 kB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798
  1. 8.800000000000000000e+01,-1.000000000000000000e+01
  2. 2.120000000000000000e+02,-1.380000000000000000e+02
  3. 3.160000000000000000e+02,-2.440000000000000000e+02
  4. 1.880000000000000000e+02,-1.170000000000000000e+02
  5. 1.480000000000000000e+02,1.000000000000000000e+01
  6. 2.000000000000000000e+01,2.600000000000000000e+01
  7. -4.800000000000000000e+01,1.140000000000000000e+02
  8. 5.400000000000000000e+01,1.720000000000000000e+02
  9. 7.600000000000000000e+01,2.320000000000000000e+02
  10. 6.600000000000000000e+01,3.220000000000000000e+02
  11. 6.800000000000000000e+01,3.180000000000000000e+02
  12. 6.000000000000000000e+01,1.900000000000000000e+02
  13. 1.800000000000000000e+01,6.200000000000000000e+01
  14. -2.600000000000000000e+01,-4.000000000000000000e+00
  15. -5.800000000000000000e+01,-1.800000000000000000e+01
  16. -3.200000000000000000e+01,-1.800000000000000000e+01
  17. -7.400000000000000000e+01,-1.200000000000000000e+01
  18. -6.800000000000000000e+01,-2.000000000000000000e+01
  19. -7.000000000000000000e+01,-2.800000000000000000e+01
  20. -8.000000000000000000e+01,-2.000000000000000000e+01
  21. -8.200000000000000000e+01,-2.600000000000000000e+01
  22. -8.400000000000000000e+01,-2.400000000000000000e+01
  23. -1.060000000000000000e+02,-2.200000000000000000e+01
  24. -1.040000000000000000e+02,-4.000000000000000000e+01
  25. -1.100000000000000000e+02,-3.000000000000000000e+01
  26. -9.600000000000000000e+01,-3.800000000000000000e+01
  27. -1.460000000000000000e+02,-5.000000000000000000e+01
  28. -1.060000000000000000e+02,-6.200000000000000000e+01
  29. -1.320000000000000000e+02,-4.600000000000000000e+01
  30. -1.220000000000000000e+02,-7.600000000000000000e+01
  31. -1.580000000000000000e+02,-7.000000000000000000e+01
  32. -1.320000000000000000e+02,-8.400000000000000000e+01
  33. -1.160000000000000000e+02,-9.000000000000000000e+01
  34. -1.300000000000000000e+02,-9.600000000000000000e+01
  35. -1.160000000000000000e+02,-9.800000000000000000e+01
  36. -9.000000000000000000e+01,-1.100000000000000000e+02
  37. -6.800000000000000000e+01,-9.800000000000000000e+01
  38. -3.400000000000000000e+01,-1.200000000000000000e+02
  39. -2.000000000000000000e+00,-9.800000000000000000e+01
  40. 0.000000000000000000e+00,-9.600000000000000000e+01
  41. 4.600000000000000000e+01,-8.200000000000000000e+01
  42. 4.800000000000000000e+01,-7.800000000000000000e+01
  43. 5.000000000000000000e+01,-6.400000000000000000e+01
  44. 8.000000000000000000e+01,-4.200000000000000000e+01
  45. 9.200000000000000000e+01,-4.000000000000000000e+01
  46. 6.800000000000000000e+01,-2.000000000000000000e+01
  47. 9.400000000000000000e+01,-2.800000000000000000e+01
  48. 7.400000000000000000e+01,-8.000000000000000000e+00
  49. 7.600000000000000000e+01,-2.600000000000000000e+01
  50. 6.600000000000000000e+01,-2.000000000000000000e+00
  51. 7.000000000000000000e+01,-1.800000000000000000e+01
  52. 6.600000000000000000e+01,8.000000000000000000e+00
  53. 4.600000000000000000e+01,-6.000000000000000000e+00
  54. 7.000000000000000000e+01,-6.000000000000000000e+00
  55. 4.000000000000000000e+01,-6.000000000000000000e+00
  56. 4.000000000000000000e+01,2.000000000000000000e+00
  57. 6.800000000000000000e+01,-4.000000000000000000e+00
  58. 4.000000000000000000e+01,0.000000000000000000e+00
  59. 5.400000000000000000e+01,2.000000000000000000e+00
  60. 4.000000000000000000e+01,-8.000000000000000000e+00
  61. 5.800000000000000000e+01,0.000000000000000000e+00
  62. 2.000000000000000000e+01,1.400000000000000000e+01
  63. 5.600000000000000000e+01,-1.600000000000000000e+01
  64. 2.600000000000000000e+01,-1.000000000000000000e+01
  65. 3.400000000000000000e+01,-2.000000000000000000e+00
  66. 3.600000000000000000e+01,-2.000000000000000000e+00
  67. 2.200000000000000000e+01,-1.000000000000000000e+01
  68. 8.000000000000000000e+00,2.000000000000000000e+00
  69. 3.200000000000000000e+01,-6.000000000000000000e+00
  70. 1.800000000000000000e+01,-4.000000000000000000e+00
  71. 6.000000000000000000e+00,8.000000000000000000e+00
  72. 2.000000000000000000e+00,-1.200000000000000000e+01
  73. 1.600000000000000000e+01,8.000000000000000000e+00
  74. 2.600000000000000000e+01,8.000000000000000000e+00
  75. 3.200000000000000000e+01,1.800000000000000000e+01
  76. 7.000000000000000000e+01,2.400000000000000000e+01
  77. 4.000000000000000000e+01,2.600000000000000000e+01
  78. 5.000000000000000000e+01,2.200000000000000000e+01
  79. 2.600000000000000000e+01,-8.000000000000000000e+00
  80. 1.400000000000000000e+01,-2.000000000000000000e+00
  81. 2.000000000000000000e+01,-2.200000000000000000e+01
  82. -1.800000000000000000e+01,-4.000000000000000000e+00
  83. -2.400000000000000000e+01,-2.000000000000000000e+01
  84. -1.200000000000000000e+01,-1.000000000000000000e+01
  85. -3.600000000000000000e+01,-1.800000000000000000e+01
  86. -1.600000000000000000e+01,-1.800000000000000000e+01
  87. -3.400000000000000000e+01,-2.000000000000000000e+00
  88. -2.200000000000000000e+01,-8.000000000000000000e+00
  89. -2.400000000000000000e+01,1.200000000000000000e+01
  90. -5.000000000000000000e+01,-6.000000000000000000e+00
  91. -2.600000000000000000e+01,-1.000000000000000000e+01
  92. -2.000000000000000000e+01,0.000000000000000000e+00
  93. -4.400000000000000000e+01,-1.200000000000000000e+01
  94. -6.000000000000000000e+00,4.000000000000000000e+00
  95. -5.000000000000000000e+01,-4.000000000000000000e+00
  96. -4.600000000000000000e+01,-1.400000000000000000e+01
  97. -2.400000000000000000e+01,6.000000000000000000e+00
  98. -1.200000000000000000e+01,3.400000000000000000e+01

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