Titlebook: Complex Pattern Mining; New Challenges, Meth Annalisa Appice,Michelangelo Ceci,Zbigniew W. Ras Book 2020 Springer Nature Switzerland AG 202

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Efficient Infrequent Pattern Mining Using Negative Itemset Tree,al database. In various practical applications such as science, medical and accident data analysis, frequent patterns usually represent obvious and expected phenomena. Really interesting information might hide in obscure rarity. Existing rare pattern mining approaches are mainly adapted from frequen

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Hierarchical Adversarial Training for Multi-domain Adaptive Sentiment Analysis,alysis usually involves multiple different domains, and the labeled data is often difficult to obtain. In this paper we propose a hierarchical adversarial neural network (HANN) for adaptive sentiment analysis. Unlike most existing deep learning based methods, the proposed method HANN is able to shar

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Optimizing C-Index via Gradient Boosting in Medical Survival Analysis,n performing survival analysis, we deal with a data set with missing values, and changes over time. Such data are difficult to be used as a basis to predict survival of patients, as these data are complex and scarce. In survival analysis methods, usually partial log likelihood is maximized following