242 / 1971-01-01 00:00:00
Cancer Classification And Biomaker Discovery Based Hybrid Bqpso/svm Algorithm
BQPSO,BPSO,GA,SVM,LOOCV
Final Paper
方云 范 / 江南大学
俊 孙 / 江南大学
In this work, a BQPSO/SVM (Quantum-Behaved Particle Swarm Optimization with Binary Encoding) algorithm for cancer feature selection is proposed. We also implement BPSO/SVM (Particle Swarm Optimization) and GA/SVM (Genetic Algorithm) to be compared with the proposed algorithm. All these three are augmented with Support Vector Machines (SVM) with Leave-one-out Cross Validation (LOOCV) and assessed on five microarray data sets (Leukemia, Prostate, Colon, Lung, Lymphoma). The results show that BQPSO/SVM has significant advantages in accuracy, robustness and the number of feature genes selected compared with the other two algorithms.
Important Date
  • Conference Date

    Jan 22

    2015

    to

    Feb 23

    2015

  • Dec 20 2014

    Draft paper submission deadline

  • Dec 20 2014

    Early Bird Registration

  • Dec 31 2014

    Final Paper Deadline

  • Feb 23 2015

    Registration deadline

  • Apr 20 2015

    Abstract Submission Deadline

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