A comprehensive survey on functional link neural networks and an adaptive PSO–BP learning for CFLNN

S Dehuri, SB Cho - Neural Computing and Applications, 2010 - Springer
Functional link neural network (FLNN) is a class of higher order neural networks (HONs) and
have gained extensive popularity in recent years. FLNN have been successfully used in …

Dengue epidemics prediction: A survey of the state-of-the-art based on data science processes

P Siriyasatien, S Chadsuthi, K Jampachaisri… - IEEE …, 2018 - ieeexplore.ieee.org
Dengue infection is a mosquitoborne disease caused by dengue viruses, which are carried
by several species of mosquito of the genus Aedes, principally Ae. aegypti. Dengue …

Towards CRISP-ML (Q): a machine learning process model with quality assurance methodology

S Studer, TB Bui, C Drescher, A Hanuschkin… - Machine learning and …, 2021 - mdpi.com
Machine learning is an established and frequently used technique in industry and
academia, but a standard process model to improve success and efficiency of machine …

A survey of data mining and knowledge discovery process models and methodologies

G Mariscal, O Marban, C Fernandez - The Knowledge Engineering …, 2010 - cambridge.org
Up to now, many data mining and knowledge discovery methodologies and process models
have been developed, with varying degrees of success. In this paper, we describe the most …

Tree ensembles for predicting structured outputs

D Kocev, C Vens, J Struyf, S Džeroski - Pattern Recognition, 2013 - Elsevier
In this paper, we address the task of learning models for predicting structured outputs. We
consider both global and local predictions of structured outputs, the former based on a …

A data-driven approach to improve customer churn prediction based on telecom customer segmentation

T Zhang, S Moro, RF Ramos - Future Internet, 2022 - mdpi.com
Numerous valuable clients can be lost to competitors in the telecommunication industry,
leading to profit loss. Thus, understanding the reasons for client churn is vital for …

Introduction to knowledge discovery and data mining

O Maimon, L Rokach - Data mining and knowledge discovery handbook, 2010 - Springer
Abstract Knowledge Discovery in Databases (KDD) is an automatic, exploratory analysis
and modeling of large data repositories. KDD is the organized process of identifying valid …

A survey on enhanced subspace clustering

K Sim, V Gopalkrishnan, A Zimek, G Cong - Data mining and knowledge …, 2013 - Springer
Subspace clustering finds sets of objects that are homogeneous in subspaces of high-
dimensional datasets, and has been successfully applied in many domains. In recent years …

Manifold elastic net: a unified framework for sparse dimension reduction

T Zhou, D Tao, X Wu - Data Mining and Knowledge Discovery, 2011 - Springer
It is difficult to find the optimal sparse solution of a manifold learning based dimensionality
reduction algorithm. The lasso or the elastic net penalized manifold learning based …

Learning from the past: automated rule generation for complex event processing

A Margara, G Cugola, G Tamburrelli - Proceedings of the 8th ACM …, 2014 - dl.acm.org
Complex Event Processing (CEP) systems aim at processing large flows of events to
discover situations of interest. In CEP, the processing takes place according to user-defined …