Hi, I have a question regarding the MLearn in MLinterface package. Assume I want to use nnet to build a nerual network prediction model. I can observe performace of various parameters in nnet using MLearn to train and cross validate with my data. Now, I want to retrive the model with best performance from my MLearn result. What should I do? I look the structure of returning result. It seems a RObject inside the MLearn returing object containing a neural model. Is this the best one? If I can nnot do this from MLearn, is there any other method or package to do this? Thanks, Best regards, Weihsin Wang, Ph.D. Bioinformatics Core Lab., Biomedical Engineering Research Lab., Industrial Technology Research Institute TEL:886-3-5913689 FAX: 886-3-5820445 ==================================================================== æœ¬ä¿¡ä»¶å¯èƒ½åŒ å«å·¥ç ”é™¢æ©Ÿå¯†è³‡è¨Šï¼ŒéžæŒ‡å®šä¹‹æ”¶ä»¶è€ ï¼Œè«‹å‹¿ä½¿ç”¨æˆ–æ­éœ²æœ¬ä¿¡ä»¶å §å®¹ï¼Œä¸¦è«‹éŠ·æ¯€æ­¤ä¿¡ä»¶ã€‚ This email may contain confidential information. Please do not use or disclose it in any way and delete it if you are not the intended recipient. [[alternative HTML version deleted]]

If you have no issues generating the expression values into a matrix or data frame, you might consider using the caret package: https://stat.ethz.ch/pipermail/r-packages/2010/001177.html There are also some functions for normalizing Affy arrays on a one-off basis that can be useeful for predictive modeling. Max On Mon, Nov 15, 2010 at 9:30 PM, <jrwang at="" itri.org.tw=""> wrote: > Hi, I have a question regarding the MLearn in MLinterface package. Assume I want to use nnet to build a nerual network prediction model. I can observe performace of various parameters in nnet using MLearn to train and cross validate with my data. Now, I want to retrive the model with best performance from my MLearn result. What should I do? I look the structure of returning result. It seems a RObject inside the MLearn returing object containing a neural model. Is this the best one? If I can nnot do this from MLearn, is there any other method or package to do this? Thanks, > > Best regards, > > Weihsin Wang, Ph.D. > Bioinformatics Core Lab., > Biomedical Engineering Research Lab., > Industrial Technology Research Institute > TEL:886-3-5913689 > FAX: 886-3-5820445 > > > ==================================================================== > ???????????????????????????????????????????? > This email may contain confidential information. Pleas...{{dropped:19}}