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image.datasetDoc.json 1.1 kB

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  1. {
  2. "about":
  3. {
  4. "datasetID": "image_dataset_1",
  5. "datasetName":"Sample Image Dataset",
  6. "humanSubjectsResearch": false,
  7. "license":"CC",
  8. "datasetSchemaVersion":"3.0",
  9. "redacted":false
  10. },
  11. "dataResources":
  12. [
  13. {
  14. "resID": "0",
  15. "resPath": "media/",
  16. "resType": "image",
  17. "resFormat": ["img/png"],
  18. "isCollection": true,
  19. },
  20. {
  21. "resID": "1",
  22. "resPath": "tables/learningDoc.csv",
  23. "resType": "table",
  24. "resFormat": ["text/csv"],
  25. "isCollection": false,
  26. "columns":[
  27. {
  28. "colIndex": 0,
  29. "colName": "d3mIndex",
  30. "colType": "integer",
  31. "role": ["index"]
  32. },
  33. {
  34. "colIndex": 1,
  35. "colName": "image",
  36. "colType": "string",
  37. "role": ["attribute"],
  38. "refersTo":{
  39. "resID": "0",
  40. "resObject": "item"
  41. }
  42. },
  43. {
  44. "colIndex": 2,
  45. "colName": "label",
  46. "colType": "categorical",
  47. "role": ["suggestedTarget"]
  48. }
  49. ]
  50. }
  51. ]
  52. }

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