在 英语 中使用 Bad data 的示例及其翻译为 中文
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So we can make sure there's no bias or bad data in that system.
Investigators later determined that two of the plane's angle-of-attack sensors had frozen in place, causing them to feed bad data.
Outliers can be the result of bad data collection, or they can be legitimate extreme values.
If a classic FIFO is used and a bad CRC occurs, all the data has to be flushed out because it's bad data.
A big challenge with online learning is that if bad data is fed to the system, the system performances will gradually decline.
With that information we were able to find the rest of the bad data and repair it.
So we can make sure there's no bias or bad data in that system.
The middleware filters the data from the reader and ensures that it is free of multiple reads or bad data.
Improve data quality, by providing consistent codes and descriptions, flagging or even fixing bad data.
There would have to be standards applied to the introduction of data in the first place: Bad data in; bad data out.
So we can make sure there's no bias or bad data in that system.
A new report from Dun& Bradstreet reveals businesses are missing revenue opportunities and losing customers due to bad data practices.
Sometimes out of sheer laziness, bad data or incompetence, we make poor decisions that cause us to fail at work.
Bad data causes all sorts of trouble- good decision making is harder, customers are angered- and it adds costs.
So we can make sure there's no bias or bad data in that system.
The characteristic of focal loss is that it can concentrate the error on the bad data of training.
The purpose of this step is to eliminate bad data(redundant, incomplete or incorrect data) and create high-quality data for the best results.
The troublesome user(“&beer&love”) who started the bad data cascade had been kicked off Wikidata before and reportedly has now been kicked off again.
We saw some terrible fiascos with the recent Microsoft Chat software being released without any controls, and users feeding it really bad data.
The old saying“garbage in, garbage out” fits perfectly here because if you have bad data, you're going to get a bad model.