Advanced Data Mining Techniques

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Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis (2014, background): “Recall in information retrieval is the fraction of the documents that are relevant to the query that are successfully retrieved [11].”
Adaptive Machine Learning for Credit Card Fraud Detection (2015, background): “Other classification measures based on the confusion matrix are [47, 48]:”
A survey on classification techniques for opinion mining and sentiment analysis (2017, methodology): “6 Evaluation criteria To evaluate the performance of different methods for text classification and sentiment analysis, four criteria are considered from information retrieval (Baeza-Yates and Ribeiro-Neto 1999; Olson and Delen 2008) including accuracy, precision, recall and f1-score which are define”
Models for early prediction of at-risk students in a course using standards-based grading (2016, methodology): “Typically, KNN, DT, and MLP modeling methods result in models with low bias and high variance (Moody, 1994; Olson & Delen, 2008).”
WHYPER: Towards Automating Risk Assessment of Mobile Applications (2013, background): “In statistical classiﬁcation [39], Precision is deﬁned as the ratio of the number of true positives to the total number of items reported to be true, and Recall is deﬁned as the ratio of the number of true positives to the total number of items that are true.”