Sentence examples for smallest number of errors from inspiring English sources
In particular, we use bagged lazy option trees (LOTs) and bagged probability estimation trees (PETs) to identify all unstable channels while making the smallest number of errors of classifying stable channels as unstable, thereby minimizing cost and maximizing safety.
The smallest number of errors in cross-validation was one error obtained when using two genes only.
Another global trend is that for all 4 simulation types, the MRN has the smallest number of errors closely followed by UpQu, Medi, TMM, TMM50, and RLE methods.
The mean absolute deviation in ranks between the direct prioritization ranking and the predicted rankings illustrates that the PTO-WAD not only produces the smallest number of errors, but also that these errors are less serious (table 4).
He was quoted this week by The Associated Press as saying that "if you are honest about the debate you have got to acknowledge there are always going to be some small number of errors".
See articleAn internal Israeli army investigation concluded that, despite a small number of errors, the army kept within the bounds of international law during the assault on the Gaza Strip three months ago.
Those who are skeptical of global warming science have been invigorated by a small number of errors in the landmark 2007 report from the United Nations Intergovernmental Panel on Climate Change.
In this, bank and insurance company chiefs were ordered to show that they had instilled a culture whereby they and their staff understood what the fair treatment of customers meant; how they expected their staff to achieve this at all times; and where (an expected relatively small number of) errors were found, they were put right and learned from.
We suspect this interaction is largely spurious, given the small number of errors overall.
Automatic conversion will usually have a small number of errors, but mainly in that fields will not be recognized, rather than corrupted.
Data curation is important for two main reasons: (1) Publically available data sets may contain multiple errors; (2) even a small number of errors may compromise the quality of QSAR models [11].
