什么是偏差检测？
Creating an interactive Cognos report for deviation detection.
为偏差检测创建交互式Cognos报告。
Correspondingly, deviation detection can be used for different tasks.
相应地，偏差检测可用于不同的任务。
In the following example, deviation detection is applied to entries about bank customers.
接下来的例子对关于银行客户的条目应用偏差检测。
InfoSphere Warehouse USES a particularly powerful method for deviation detection that is based on data clustering.
InfoSphereWarehouse使用一种特别强大的方法来进行偏差检测，这种方法基于数据集群。
So, the phase deviation detection is of great importance in BMIT imaging system.
因此，对相位差的检测成为BMIT成像系统中的核心问题。
In the following, learn how InfoSphere Warehouse detects outliers and how you can apply deviation detection to your data.
接下来将了解InfoSphere Warehouse如何检测离群值，以及如何对数据应用偏差检测。
This can be used for fraud detection, which is, together with data cleansing, the second major application of deviation detection.
这可用于检测欺诈，这是偏差检测的第二个主要应用。
How to define "unusual" exactly is subject to academic debate and may also depend on the domain where deviation detection is applied.
“异常”的确切定义还有待讨论，但它与应用偏差检测的领域有关。
This flow simply loads the customer table, passes it to the deviation detection algorithm, and writes the results into a new table (see Figure 3).
这个流装载客户表，将它传递到偏差检测算法，并将结果写到一个新表中(如图3所示)。
If you assume that your dataset contains incorrect data, then you can apply deviation detection for data cleansing, thereby finding incorrect entries in your database.
如果您猜测数据集包含不正确的数据，那么可以应用偏差检测进行数据清洗，从而发现数据库中不正确的条目。
The problem of outlier mining has been variously called outlier analysis, anomaly detection, exception mining, detecting rare events, mining rare classes, deviation detection, etc.
孤立点挖掘又称孤立点分析、异常检测、例外挖掘、小事件检测、挖掘极小类、偏差检测。
This paper presents an algorithm combining scan line and region-growing method based on video images analysis, in which lane-marking recognition and driving deviation detection are realized.
为了实时检测到行车偏移信息，提出了一种基于扫描线与区域生长相结合的视频图像分析算法，从而实现了多种道路车道标线和行车偏移的自动检测。
Deviation detection is defined as the task of finding unusual data records in large datasets.
偏差检测是一项在大型数据集中发现异常数据记录的任务。
Deviation detection is a highly interactive task, and outliers must usually be checked manually to see whether they indicate fraud, errors in the data, or some interesting opportunity.
偏差检测是高度交互性的任务，通常需要手动检查离群值，以查明是否存在欺诈倾向、数据错误或者潜在的机遇。
Deviation detection is a highly interactive task, and outliers must usually be checked manually to see whether they indicate fraud, errors in the data, or some interesting opportunity.
偏差检测是高度交互性的任务，通常需要手动检查离群值，以查明是否存在欺诈倾向、数据错误或者潜在的机遇。
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