The TDMR Package: Tuned Data Mining in R
暂无分享,去创建一个
[1] M. Powell. A New Algorithm for Unconstrained Optimization , 1970 .
[2] Richard J. Beckman,et al. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.
[3] Thomas Lengauer,et al. ROCR: visualizing classifier performance in R , 2005, Bioinform..
[4] Nikolaus Hansen,et al. The CMA Evolution Strategy: A Comparing Review , 2006, Towards a New Evolutionary Computation.
[5] Thomas Bartz-Beielstein,et al. Parameter-Tuned Data Mining: A General Framework , 2010 .
[6] Thomas Bartz-Beielstein,et al. SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization , 2010, ArXiv.
[7] Wolfgang Konen,et al. Self-configuration from a Machine-Learning Perspective , 2011, ArXiv.
[8] Thomas Bartz-Beielstein,et al. Tuned data mining: a benchmark study on different tuners , 2011, GECCO '11.
[9] Bernd Bischl,et al. Tuning and evolution of support vector kernels , 2012, Evol. Intell..
[10] Wolfgang Konen,et al. Efficient Sampling and Handling of Variance in Tuning Data Mining Models , 2012, PPSN.
[11] W. Konen,et al. Subsampling strategies in SVM ensembles , 2013 .
[12] Wolfgang Konen,et al. SVM Ensembles Are Better When Different Kernel Types Are Combined , 2013, ECDA.
[13] Thomas Bäck,et al. Efficient multi-criteria optimization on noisy machine learning problems , 2015, Appl. Soft Comput..
[14] C. X. Kou,et al. A Modified Self-Scaling Memoryless Broyden–Fletcher–Goldfarb–Shanno Method for Unconstrained Optimization , 2015, J. Optim. Theory Appl..