Quantification in Social Network
Quantification is closely related to classification: however, the goal of classification is different, since in classification we are interested in correctly guessing the true class label of each single individual. Instead, in quantification we are interested in classifying our individuals with the goal of estimating the class prevalence where is not strictly necessary to classify correctly each single individual. Classification and quantification are different because, a perfect classifier is also a perfect quantifier, not necessarily a good classifier is also good quantifier.
Quantification aims at finding the class frequencies in a set of unlabeled data, while classification aims at determining the class of each specific item in the same dataset. In other words, a quantifier does not care about perfectly predicting the class of a single item, but to guess the global trend of the classes in a new set of data.
Quantification aims at finding the class frequencies in a set of unlabeled data, while classification aims at determining the class of each specific item in the same dataset. In other words, a quantifier does not care about perfectly predicting the class of a single item, but to guess the global trend of the classes in a new set of data.
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