(AI) discipline which achieved recognition as a discipline in the early 50's. The AI objective is to understand human intelligence and to develop intelligent systems. Machine Learning (ML) focuses on the ability of learning and gained momentum in the early 80's with rule induction (also known...
Partly motivated by the mentioned industrial use case, we focus on rule learning as an easy way to provide transparency and explainability to the obtained classification. Here, in contrast to highly interesting and more sophisticated approaches studied eg. in the context of rule induction or neuro-...
(ML) techniques for manufacturing problems, starting with rule induction in symbolic domains and pattern recognition techniques in numerical, subsymbolic domains... C Egresits,L Monostori,J Hornyák - 《Journal of Intelligent Manufacturing》 被引量: 27发表: 1998年 Experimental Comparison of Symbolic...
In this paper we propose a Machine Learning (ML) methodology for predicting go-arounds events occurrence, caused by meteorological events in airports. The proposed approach makes use of an ensemble of decision-rules and neural networks. Specifically, we use the Patient Rule Induction Method (PRIM...
In this paper, we will use the Patient Rule Induction Method (PRIM) based bump hunting method to identify the spaces of higher modes and masses to indicate the peak anomalies in the CMS 2014 dataset. By applying our framework, we can find a way to observe anomalies, which can be ...
Following an IP administration of a cocktail solution of ketamine (80 mg kg−1) and xylazine (8 mg kg−1), rats were placed in an isoflurane induction chamber for 5–10 min. Then rats were moved to a stereotactic frame and their nose was placed in a cone, which provided...
And generalized rule induction (GRI) was integrated to establish association rules which can give an understanding of the relationship between cancer classes and influence genes. In addition, the outcomes obtained from the three functions of selector, classification and rule development can be ...
Autophagic induction in pathogenic conditions could have substantial benefits of therapy, including the degradation of cytotoxic materials, such as misfolded protein aggregates. Many small molecules that induce autophagy are now available. Rapamycin is a representative autophagy inducer that exerts its effica...
In fact, much of the research on learning such models has been motivated with their interpretability. For example, Fürnkranz et al. (2012) argue that rules “offer the best trade-off between human and machine understandability”. Similarly, it has been argued that rule induction offers a ...
Informally, rule learning denotes all algorithms that learn or discover patterns in data, which are formulated in the form of arule. These can be predictive (e.g.,classification rules) or descriptive rules (e.g.,association rulesorsupervised descriptive rule induction). Consequently, the learning...