We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Numerous data mining problems involve an investigation of associations between features in heterogeneous datasets, where different prediction models can be more suitable for differ...
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Pan...
Abstract. Smooth boosting algorithms are variants of boosting methods which handle only smooth distributions on the data. They are proved to be noise-tolerant and can be used in th...
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...