... 含有错误的预测 biased forecast 预测错误数据 PED PredictionErrorData 预测错误, 判断错误 be off the mark ...
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经过多年对瘦客户机,清楚系统垃圾,简体软件的错误预测,还以为以云计算为基础的数据和服务不会成为现实。而现在,就是它真正到来的时刻。
It's the real arrival, after years of false predictions, of the thin client, running clean, simple software, against cloud-based data and services.
预测的误差可能来自错误的数据、错误的假设或错误的模型。
Errors in forecasting can result from bad data, wrong assumptions or a faulty model.
第一,使用真实数据更容易定位错误,因为真实数据比开发期间使用的测试数据更难预测。
The first is that you are more likely to spot errors if you are using real-world data, because it is more unpredictable than the test data used during development.
In particular, a very common thing people do with data is they extrapolate.
这种错误,在数据预测时,很常见。
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