search for: coreaff

As a follow-up to my email below: The input data frame to nnet() has dimensions: > dim(coreaff.trn.nn) [1] 5088 8 And the predictions from the neural network (35 records are dropped - see email below for more details) has dimensions: > pred <- predict(coreaff.nn1) > dim(pred) [1] 5053 1 So, the following line of R code does not work as the dimensions are differe...

...________________________ From: Ryan, Jude Sent: Tuesday, May 12, 2009 1:23 PM To: 'r-help at r-project.org' Cc: juderyan61 at yahoo.com Subject: FW: neural network not using all observations As a follow-up to my email below: The input data frame to nnet() has dimensions: > dim(coreaff.trn.nn) [1] 5088 8 And the predictions from the neural network (35 records are dropped - see email below for more details) has dimensions: > pred <- predict(coreaff.nn1) > dim(pred) [1] 5053 1 So, the following line of R code does not work as the dimensions are different....

...gression on the same variables shown below gives me an R-Square of about 0.12. I am trying to increase the predictive power of this regression model with a neural network being careful to avoid overfitting. Similar to Venables and Ripley, I used the following code: > library(nnet) > dim(coreaff.trn.nn) [1] 5088 8 > head(coreaff.trn.nn) hh.iast.y WC_Total_Assets all_assets_per_hh age tenure max_acc_ownr_liq_asts_n_med max_acc_ownr_nwrth_n_med max_acc_ownr_ann_incm_n_med 1 3059448 -0.4692186 -0.4173532 -0.06599001 -1.04747935 0 1...

Hi All, I am trying to learn Neural Networks. I found that R has packages which can help build Neural Nets - the popular one being AMORE package. Is there any book / resource available which guides us in this subject using the AMORE package? Any help will be much appreciated. Thanks, Indrajit