A drift detection method based on dynamic classifier selection
Sign Up to like & getrecommendations! Published in 2019 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-019-00656-w
Abstract: Machine learning algorithms can be applied to several practical problems, such as spam, fraud and intrusion detection, and customer preferences, among others. In most of these problems, data come in streams, which mean that data… read more here.
Keywords: drift; detection; drift detection; method ... See more keywords
Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical theory and computation"
DOI: 10.48550/arxiv.2203.01276
Abstract: Virtual high-throughput screening (VHTS) and machine learning (ML) have greatly accelerated the design of single-site transition-metal catalysts. VHTS of catalysts, however, is often accompanied with a high calculation failure rate and wasted computational resources due… read more here.
Keywords: reactive intermediates; dynamic classifier; machine learning; geometry ... See more keywords