Sentence examples for wrongly trained from inspiring English sources

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The malfunctioning monitor and the wrongly trained intensivist may be a great risk for the patient!

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Commanders assumed, wrongly, that forces trained to fight high-intensity battles could also handle low-intensity conflicts.One cavalry officer, Lieut-Colonel Paul Yingling, has denounced the failure of America's generals in Iraq as in Vietnam to prepare the army for counter-insurgency.

Lotfi Raissi, the Algerian wrongly accused of training pilots involved in the 9/11 terrorist attacks in New York, was given the go-ahead yesterday to renew his bid for government compensation for "serious defaults" by police and the Crown Prosecution Service.

Meulensteen said: "Unfortunately he kicked a ball wrongly in training which aggravated something in his groin as far as I'm aware.

A climate of suspicion had built up, she suggested, with many of those being tested wrongly believing that the assessors were not trained and would "treat them with contempt".

PolyPhen-2 trained on the HumDiv dataset wrongly predicted the benign mutation as deleterious, but confused only one disease causing mutation (CYP11B1 M88I).

He criticised the way officers were trained for the use of force, saying they wrongly believing "proportionality" means "reciprocity".

Therefore, although each sub-BPNN is only trained by a portion of the original training data which may lead to the wrongly classification, the final voted classification result of a number of sub-BPNNs has a higher chance to be correct with higher efficiency for dealing with a large volume of data.

The word 'discipline' is regularly and wrongly bandied about in this context as if you can manage young people's learning by pretending they're being trained as soldiers, expected to obey without question and not to think for themselves.

A man whose life was ruined after being wrongly imprisoned over allegations that he helped to train five of the 11 September terrorists is to be awarded substantial compensation by the Government.

In the former approach, we identify instances from the training corpus that are wrongly classified according to the test corpus and train a new classifier after removing such misleading instances.

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