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26 relations: Binary classification, BLEU, C. J. van Rijsbergen, Cohen's kappa, Document classification, Fowlkes–Mallows index, Geometric mean, Harmonic mean, Information retrieval, Machine learning, Matthews correlation coefficient, METEOR, Named-entity recognition, NIST (metric), Precision and recall, Receiver operating characteristic, ROUGE (metric), Sørensen–Dice coefficient, Statistics, Text segmentation, Type I and type II errors, Uncertainty coefficient, Web query classification, Web search engine, Word error rate, Youden's J statistic.
Binary classification
Binary or binomial classification is the task of classifying the elements of a given set into two groups (predicting which group each one belongs to) on the basis of a classification rule.
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BLEU
BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another.
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C. J. van Rijsbergen
C.
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Cohen's kappa
Cohen's kappa coefficient (κ) is a statistic which measures inter-rater agreement for qualitative (categorical) items.
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Document classification
Document classification or document categorization is a problem in library science, information science and computer science.
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Fowlkes–Mallows index
Fowlkes–Mallows index is an external evaluation method that is used to determine the similarity between two clusterings (clusters obtained after a clustering algorithm).
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Geometric mean
In mathematics, the geometric mean is a mean or average, which indicates the central tendency or typical value of a set of numbers by using the product of their values (as opposed to the arithmetic mean which uses their sum).
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Harmonic mean
In mathematics, the harmonic mean (sometimes called the subcontrary mean) is one of several kinds of average, and in particular one of the Pythagorean means.
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Information retrieval
Information retrieval (IR) is the activity of obtaining information system resources relevant to an information need from a collection of information resources.
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Machine learning
Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
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Matthews correlation coefficient
The Matthews correlation coefficient is used in machine learning as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975.
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METEOR
METEOR (Metric for Evaluation of Translation with Explicit ORdering) is a metric for the evaluation of machine translation output.
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Named-entity recognition
Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
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NIST (metric)
NIST is a method for evaluating the quality of text which has been translated using machine translation.
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Precision and recall
In pattern recognition, information retrieval and binary classification, precision (also called positive predictive value) is the fraction of relevant instances among the retrieved instances, while recall (also known as sensitivity) is the fraction of relevant instances that have been retrieved over the total amount of relevant instances.
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Receiver operating characteristic
In statistics, a receiver operating characteristic curve, i.e. ROC curve, is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied.
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ROUGE (metric)
ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics and a software package used for evaluating automatic summarization and machine translation software in natural language processing.
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Sørensen–Dice coefficient
The Sørensen–Dice index, also known by other names (see Name, below), is a statistic used for comparing the similarity of two samples.
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Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.
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Text segmentation
Text segmentation is the process of dividing written text into meaningful units, such as words, sentences, or topics.
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Type I and type II errors
In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding), while a type II error is failing to reject a false null hypothesis (also known as a "false negative" finding).
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Uncertainty coefficient
In statistics, the uncertainty coefficient, also called proficiency, entropy coefficient or Theil's U, is a measure of nominal association.
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Web query classification
A Web query topic classification/categorization is a problem in information science.
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Web search engine
A web search engine is a software system that is designed to search for information on the World Wide Web.
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Word error rate
Word error rate (WER) is a common metric of the performance of a speech recognition or machine translation system.
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Youden's J statistic
Youden's J statistic (also called Youden's index) is a single statistic that captures the performance of a dichotomous diagnostic test.
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References
[1] https://en.wikipedia.org/wiki/F1_score
