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Accuracy is also used as a statistical measure of how well a binary classification test correctly identifies or excludes a condition. That is, the accuracy is the proportion of correct predictions (both true positives and true negatives) among the total number of cases examined. [10]
In addition to Hindi-Urdu, there have been attempts to design Indo-Pakistani transliteration systems for digraphic languages like Sindhi (written in extended Perso-Arabic in Sindh of Pakistan and in Devanagari by Sindhis in partitioned India), Punjabi (written in Gurmukhi in East Punjab and Shahmukhi in West Punjab), Saraiki (written in ...
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
[3] In 1982, a translation of 700 couplets of the Kural text was published under the title "Satsai." [ 3 ] There was yet another Hindi translation in 1989. [ 3 ] In 1990, T. E. S. Raghavan rendered a poetic rendition in couplet form in 'Venba' metre as in the source, following four words in the first line and three in the second. [ 5 ]
BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU.
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).
NIST is a method for evaluating the quality of text which has been translated using machine translation. Its name comes from the US National Institute of Standards and Technology . It is based on the BLEU metric, but with some alterations.
Of these, octuple-precision format is rarely used. The single- and double-precision formats are most widely used and supported on nearly all platforms. The use of half-precision format has been increasing especially in the field of machine learning since many machine learning algorithms are inherently error-tolerant.