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| Drawing1.vsdx | 5 years ago | |
| allViews.PNG | 5 years ago | |
| examples.txt | 5 years ago | |
| objDetection_scoring_GT.PNG | 5 years ago | |
| objDetection_scoring_PRED.PNG | 5 years ago | |
| sampleDataSplitsFile.PNG | 5 years ago | |
| sampleDataset.PNG | 5 years ago | |
| sampleProblem.PNG | 5 years ago | |
| sampleProblemTestView.PNG | 5 years ago | |
| sampleProblemTrainView.PNG | 5 years ago | |
| sampleProblem_objectDetection.PNG | 5 years ago | |
| sampleSupply.PNG | 5 years ago | |
| sampleTestView.PNG | 5 years ago | |
| sampleTrainView.PNG | 5 years ago | |
| schema fields spreadsheet.xlsx | 5 years ago | |
| testView.PNG | 5 years ago | |
| trainView.PNG | 5 years ago | |
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
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