APA (7th ed.) Citation

Cannon, E. O., Amini, A., Bender, A., Sternberg, M. J. E., Muggleton, S. H., Glen, R. C., & Mitchell, J. B. O. (2007). Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds. Journal of computer-aided molecular design, 21(5), 269-280. https://doi.org/10.1007/s10822-007-9113-3

Chicago Style (17th ed.) Citation

Cannon, Edward O., Ata Amini, Andreas Bender, Michael J. E. Sternberg, Stephen H. Muggleton, Robert C. Glen, and John B. O. Mitchell. "Support Vector Inductive Logic Programming Outperforms the Naive Bayes Classifier and Inductive Logic Programming for the Classification of Bioactive Chemical Compounds." Journal of Computer-aided Molecular Design 21, no. 5 (2007): 269-280. https://doi.org/10.1007/s10822-007-9113-3.

MLA (9th ed.) Citation

Cannon, Edward O., et al. "Support Vector Inductive Logic Programming Outperforms the Naive Bayes Classifier and Inductive Logic Programming for the Classification of Bioactive Chemical Compounds." Journal of Computer-aided Molecular Design, vol. 21, no. 5, 2007, pp. 269-280, https://doi.org/10.1007/s10822-007-9113-3.