Today, the limelight is on Deep Learning. With the huge success of deep learning, other machine learning paradigms have had to take the backstage. Yet other models, particularly rule-based learning ..
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Abstract:
Today, the limelight is on Deep Learning. With the huge success of deep learning, other machine learning paradigms have had to take the backstage. Yet other models, particularly rule-based learning methods, are more readable and explainable and can even be competitive when labelled data is not abundant, and therefore could be more suitable for some applications where transparency is a must. One such rule-based method is the less-known Associative Classifier. The power of associative classifiers is to determine patterns from the data and perform classification based on the features most indicative of prediction. Early approaches suffer from cumbersome thresholds requiring prior knowledge. We will present a new associative classifier approach that is even more accurate while generating a smaller model. It can also be used in an explainable-AI pipeline to explain inferences from other classifiers, irrespective of the predictive model used inside the black box.
Bio:
Osmar R. Zaïane is a Professor in Computing Science at the University of Alberta, Canada, Fellow of the Alberta Machine Intelligence Institute (Amii), and Canada CIFAR AI Chair. He is also a Fellow of the Canadian Academy of Engineering. Dr. Zaiane obtained his Ph.D. from Simon Fraser University, Canada, in 1999. He has published more than 400 papers in refereed international conferences and journals. He is Associate Editor of many International Journals on data mining and data analytics and served as program chair and general chair for scores of international conferences in the field of knowledge discovery and data mining. Dr. Zaiane received numerous awards including the Killam Professorship award, the McCalla Research Professorship, and the ACM SIGKDD Service Award from the ACM Special Interest Group on Data Mining, which runs the world’s premier data science, big data, and data mining association and conference.
Host: Dr.Jundong Li
Organizer: Cong Shen