Advancing post-genome data and system integration through machine learning

Evaluating the efficiency of system inte

Evaluating the efficiency of system integration projects using data envelopment analysis (DEA) and machine learning

✍ Han Kook Hong; Sung Ho Ha; Chung Kwan Shin; Sang Chan Park; Soung Hie Kim 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 367 KB

Data envelopment analysis (DEA), a non-parametric productivity analysis, has become an accepted approach for assessing efficiency in a wide range of fields. Despite its extensive applications, some features of DEA remain unexploited. We aim to show that DEA can be used to evaluate the efficiency of