Copyright
©The Author(s) 2018.
World J Clin Oncol. Sep 14, 2018; 9(5): 98-109
Published online Sep 14, 2018. doi: 10.5306/wjco.v9.i5.98
Published online Sep 14, 2018. doi: 10.5306/wjco.v9.i5.98
Figure 6 Bayesian rule learning generated rule model with λ=8 (highest average area under the receiver operator characteristics curve) on the real-world lung cancer prognostic dataset.
TP: True positives; FP: False positives; Pos: Total number of examples that match the rules consequent target value; Neg: Total number that do not match the right hand side of the rule; EGFR: Epidermal growth factor receptor.
- Citation: Balasubramanian JB, Gopalakrishnan V. Tunable structure priors for Bayesian rule learning for knowledge integrated biomarker discovery. World J Clin Oncol 2018; 9(5): 98-109
- URL: https://www.wjgnet.com/2218-4333/full/v9/i5/98.htm
- DOI: https://dx.doi.org/10.5306/wjco.v9.i5.98