TY - JOUR
T1 - CEKA
T2 - A tool for mining the wisdom of crowds
AU - Zhang, Jing
AU - Sheng, Victor S.
AU - Nicholson, Bryce A.
AU - Wu, Xindong
N1 - Publisher Copyright:
© 2015 Jing Zhang, Victor S. Sheng, Bryce A. Nicholson, and Xindong Wu.
PY - 2015/12
Y1 - 2015/12
N2 - CEKA is a software package for developers and researchers to mine the wisdom of crowds. It makes the entire knowledge discovery procedure much easier, including analyzing qualities of workers, simulating labeling behaviors, inferring true class labels of instances, filtering and correcting mislabeled instances (noise), building learning models and evaluating them. It integrates a set of state-of-the-art inference algorithms, a set of general noise handling algorithms, and abundant functions for model training and evaluation. CEKA is written in Java with core classes being compatible with the well-known machine learning tool WEKA, which makes the utilization of the functions in WEKA much easier.
AB - CEKA is a software package for developers and researchers to mine the wisdom of crowds. It makes the entire knowledge discovery procedure much easier, including analyzing qualities of workers, simulating labeling behaviors, inferring true class labels of instances, filtering and correcting mislabeled instances (noise), building learning models and evaluating them. It integrates a set of state-of-the-art inference algorithms, a set of general noise handling algorithms, and abundant functions for model training and evaluation. CEKA is written in Java with core classes being compatible with the well-known machine learning tool WEKA, which makes the utilization of the functions in WEKA much easier.
KW - Crowdsourcing
KW - Inference
KW - Learning from crowds
KW - Multiple noisy labeling
KW - Noise handling
KW - Repeated labeling simulation
UR - http://www.scopus.com/inward/record.url?scp=84961574739&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84961574739
SN - 1532-4435
VL - 16
SP - 2853
EP - 2858
JO - Journal of Machine Learning Research
JF - Journal of Machine Learning Research
ER -