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.

163.csv 5.1 kB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100
  1. 3.200000000000000000e+01,2.000000000000000000e+01
  2. 7.000000000000000000e+01,-1.400000000000000000e+01
  3. 1.900000000000000000e+02,-1.420000000000000000e+02
  4. 3.170000000000000000e+02,-2.100000000000000000e+02
  5. 1.890000000000000000e+02,-8.300000000000000000e+01
  6. 1.660000000000000000e+02,4.400000000000000000e+01
  7. 3.800000000000000000e+01,6.800000000000000000e+01
  8. -2.000000000000000000e+00,1.280000000000000000e+02
  9. 7.000000000000000000e+01,1.780000000000000000e+02
  10. 9.400000000000000000e+01,2.600000000000000000e+02
  11. 6.200000000000000000e+01,3.360000000000000000e+02
  12. 6.000000000000000000e+01,2.700000000000000000e+02
  13. 5.000000000000000000e+01,1.420000000000000000e+02
  14. -1.600000000000000000e+01,1.400000000000000000e+01
  15. -5.200000000000000000e+01,-6.000000000000000000e+00
  16. -6.200000000000000000e+01,-1.200000000000000000e+01
  17. -7.800000000000000000e+01,-1.200000000000000000e+01
  18. -8.600000000000000000e+01,-2.600000000000000000e+01
  19. -9.000000000000000000e+01,-1.200000000000000000e+01
  20. -8.800000000000000000e+01,-2.600000000000000000e+01
  21. -9.400000000000000000e+01,-2.000000000000000000e+01
  22. -1.120000000000000000e+02,-2.200000000000000000e+01
  23. -1.060000000000000000e+02,-2.200000000000000000e+01
  24. -1.160000000000000000e+02,-2.200000000000000000e+01
  25. -1.200000000000000000e+02,-2.800000000000000000e+01
  26. -1.300000000000000000e+02,-3.200000000000000000e+01
  27. -1.300000000000000000e+02,-4.200000000000000000e+01
  28. -1.540000000000000000e+02,-3.800000000000000000e+01
  29. -1.560000000000000000e+02,-4.400000000000000000e+01
  30. -1.620000000000000000e+02,-5.600000000000000000e+01
  31. -1.640000000000000000e+02,-6.400000000000000000e+01
  32. -1.720000000000000000e+02,-6.800000000000000000e+01
  33. -1.800000000000000000e+02,-8.600000000000000000e+01
  34. -1.720000000000000000e+02,-8.600000000000000000e+01
  35. -1.720000000000000000e+02,-9.600000000000000000e+01
  36. -1.640000000000000000e+02,-1.100000000000000000e+02
  37. -1.520000000000000000e+02,-1.100000000000000000e+02
  38. -1.240000000000000000e+02,-1.160000000000000000e+02
  39. -9.800000000000000000e+01,-1.140000000000000000e+02
  40. -7.600000000000000000e+01,-1.100000000000000000e+02
  41. -5.000000000000000000e+01,-1.040000000000000000e+02
  42. -1.600000000000000000e+01,-9.000000000000000000e+01
  43. 8.000000000000000000e+00,-8.000000000000000000e+01
  44. 2.200000000000000000e+01,-6.800000000000000000e+01
  45. 3.800000000000000000e+01,-6.400000000000000000e+01
  46. 5.800000000000000000e+01,-3.400000000000000000e+01
  47. 6.400000000000000000e+01,-4.000000000000000000e+01
  48. 6.200000000000000000e+01,-2.400000000000000000e+01
  49. 7.000000000000000000e+01,-1.800000000000000000e+01
  50. 6.200000000000000000e+01,-2.000000000000000000e+01
  51. 6.200000000000000000e+01,-1.000000000000000000e+01
  52. 4.800000000000000000e+01,-4.000000000000000000e+00
  53. 4.200000000000000000e+01,-1.000000000000000000e+01
  54. 4.200000000000000000e+01,-1.400000000000000000e+01
  55. 4.600000000000000000e+01,1.200000000000000000e+01
  56. 4.000000000000000000e+01,-2.000000000000000000e+01
  57. 3.800000000000000000e+01,6.000000000000000000e+00
  58. 3.000000000000000000e+01,-1.200000000000000000e+01
  59. 4.400000000000000000e+01,-6.000000000000000000e+00
  60. 3.200000000000000000e+01,-4.000000000000000000e+00
  61. 3.000000000000000000e+01,0.000000000000000000e+00
  62. 3.400000000000000000e+01,-6.000000000000000000e+00
  63. 2.600000000000000000e+01,-4.000000000000000000e+00
  64. 2.400000000000000000e+01,-4.000000000000000000e+00
  65. 2.000000000000000000e+01,-4.000000000000000000e+00
  66. 2.400000000000000000e+01,0.000000000000000000e+00
  67. 1.800000000000000000e+01,-4.000000000000000000e+00
  68. 1.600000000000000000e+01,-1.200000000000000000e+01
  69. 6.000000000000000000e+00,-6.000000000000000000e+00
  70. 1.200000000000000000e+01,-2.000000000000000000e+00
  71. 1.400000000000000000e+01,-6.000000000000000000e+00
  72. 4.000000000000000000e+00,-2.000000000000000000e+00
  73. -4.000000000000000000e+00,-4.000000000000000000e+00
  74. 8.000000000000000000e+00,-6.000000000000000000e+00
  75. 2.000000000000000000e+00,-6.000000000000000000e+00
  76. -8.000000000000000000e+00,6.000000000000000000e+00
  77. 1.000000000000000000e+01,1.000000000000000000e+01
  78. 3.000000000000000000e+01,8.000000000000000000e+00
  79. 4.200000000000000000e+01,2.800000000000000000e+01
  80. 4.000000000000000000e+01,1.600000000000000000e+01
  81. 2.400000000000000000e+01,1.200000000000000000e+01
  82. 1.400000000000000000e+01,2.000000000000000000e+00
  83. 1.800000000000000000e+01,-6.000000000000000000e+00
  84. -8.000000000000000000e+00,-1.600000000000000000e+01
  85. -1.200000000000000000e+01,-1.200000000000000000e+01
  86. -1.400000000000000000e+01,-1.600000000000000000e+01
  87. -2.200000000000000000e+01,-1.600000000000000000e+01
  88. -2.800000000000000000e+01,-2.400000000000000000e+01
  89. -2.600000000000000000e+01,-4.000000000000000000e+00
  90. -2.200000000000000000e+01,-6.000000000000000000e+00
  91. -2.800000000000000000e+01,-8.000000000000000000e+00
  92. -3.000000000000000000e+01,-8.000000000000000000e+00
  93. -3.800000000000000000e+01,-8.000000000000000000e+00
  94. -2.600000000000000000e+01,-2.000000000000000000e+00
  95. -2.800000000000000000e+01,-1.000000000000000000e+01
  96. -3.600000000000000000e+01,-4.000000000000000000e+00
  97. -3.200000000000000000e+01,-1.200000000000000000e+01
  98. -2.600000000000000000e+01,-1.200000000000000000e+01
  99. -2.800000000000000000e+01,0.000000000000000000e+00
  100. -1.600000000000000000e+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