Sentence examples for bias machine from inspiring English sources

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"Basically the only place that these financial guys consider factual enough for rebroadcast is the one part of the Rupert Murdoch bias machine explicitly labeled opinion".

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Secondly, the number of non-interaction sites is much more than interaction sites, which leads to a sample imbalance problem, and hence biased machine learning model with preference to non-interaction sites.

But we shouldn't be surprised: Google has actually been pretty candid about the possibility for bias in machine learning systems, and how to counter it or build inclusivity in from the start.

It was nice to see Google paying a lot of attention to identifying and mitigating implicit bias in machine-learning models and algorithms; it was nice to see that the crowd was, by tech standards, impressively diverse; it was really excellent to see a panel like this one —.

Likewise, many methods have been developed to deal with selection bias, including machine-learning methods such as genetic matching, 66 and classification and regression trees.

Republicans answer that human vote counting, in this case mainly by Democrats eager to help their candidate catch up, is prone to human misjudgment or bias; that the machine recount was consistent, impartial and made on time; and that to change election rules and set new standards for counting a few counties after the election deprives most Florida voters of equal rights.

One solution could be to offset machine bias in the same way that we have done with humans.

Recent research underscores this machine bias, showing that commercial facial-recognition systems excel at identifying light-skinned males, with an error rate of less than 1percentt.

Incomplete and duplicate sequences were removed to minimize bias in the machine learning training process.

However, to minimise bias, the OPT machine that was used for all the patients was regularly calibrated, and its distortion was independently determined to be below 15%.

Even the most carefully performed, targeted GC-MS analysis, using isotopically labelled internal standards for the analysed metabolites can result in CVs of 30% [ 6] and a less targeted approach will almost certainly introduce a high chance of machine bias in metabolomic analyses.

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