similar to: Final models from caret's train function

Hello, When evaluating different learning methods for a categorization problem with the (really useful!) caret package, I'm getting confusing results from the Kappa computation. The data is about 20,000 rows and a few dozen columns, and the categories are quite asymmetrical, 4.1% in one category and 95.9% in the other. When I train a ctree model as: model <- train(dat.dts,

Dear all, I have a question regarding the output of the coxph function. What does the 'max possible' exactly mean in the output below? Many thanks. coef exp(coef) se(coef) robust se z Pr(>|z|) smocc_zyban -0.4384 0.6451 0.8667 0.9473 -0.463 0.644 self 1.1857 3.2728 0.1405 0.1443 8.216 2.22e-16 *** smocc_zyban:self

Dear List, I need to print out each of 'k' levels of a factor 'n' times each, where 'n' is the number of elements belonging to each factor. I know that this can normally be done using the gl() command, but in my case, each level 'k' has an unequal number of elements. Example with code is as below: vc<-read.table("P:\\Transit\\CORRECT

Hi, I'm trying to extract the rules from every tree in the random forest model that I've created. I've used randomForest2Rules function from "rattle" package however I get an error "Error in if (var.class == "character" | var.class == "factor") { : argument is of length zero" Sample code: library(rattle) library(randomForest) iris.10tree

Hi, I've this dataframe: V1 V5 V6 1 MOD13Q1_2000049 0.1723 A1 2 MOD13Q1_2000049 0.1824 B1 3 MOD13Q1_2000049 0.1824 C1 4 MOD13Q1_2000049 0.1774 A2 5 MOD13Q1_2000049 0.1953 B2 6 MOD13Q1_2000049 0.1824 C2 7 MOD13Q1_2000065 0.1921 A1 8 MOD13Q1_2000065 0.1938 B1 9 MOD13Q1_2000065 0.2009 C1 10 MOD13Q1_2000065 0.2035 A2 11 MOD13Q1_2000065 0.2157 B2 12

Are there any utilities/packages for showing various performance metrics of a regression model on some labeled test data? Basic stuff I can easily write like RMSE, R-squared, etc., but maybe with some extra utilities for visualization, or reporting the distribution of prediction confidence/variance, or other things I haven't thought of. This is usually reported in most training utilities

Three more packages will be showing up on your mirror soon. The caret package (short for "Classification And REgression Training") aims to simplify the model building process. The package has functions for - data splitting: balanced train/test splits, cross-validation and bootstrapping sampling functions. There is also a function for maximum dissimilarity sampling. -

Three more packages will be showing up on your mirror soon. The caret package (short for "Classification And REgression Training") aims to simplify the model building process. The package has functions for - data splitting: balanced train/test splits, cross-validation and bootstrapping sampling functions. There is also a function for maximum dissimilarity sampling. -

Version 4.06 of the caret package was sent to CRAN. caret can be used to tune the parameters of predictive models using resampling, estimate variable importance and visualize the results. There are also various modeling and "helper" functions that can be useful for training models. caret has wrappers to over 50 different models for classification and regression. See the package

Version 4.06 of the caret package was sent to CRAN. caret can be used to tune the parameters of predictive models using resampling, estimate variable importance and visualize the results. There are also various modeling and "helper" functions that can be useful for training models. caret has wrappers to over 50 different models for classification and regression. See the package

Version 4.63 of the caret package is now on CRAN. caret can be used to tune the parameters of predictive models using resampling, estimate variable importance and visualize the results. There are also various modeling and "helper" functions that can be useful for training models. caret has wrappers to over 99 different models for classification and regression. See the package vignettes

Version 4.63 of the caret package is now on CRAN. caret can be used to tune the parameters of predictive models using resampling, estimate variable importance and visualize the results. There are also various modeling and "helper" functions that can be useful for training models. caret has wrappers to over 99 different models for classification and regression. See the package vignettes

Max and List, Could you advise me if I am using the proper caret syntax to carry out leave-one-out cross validation. In the example below, I use example data from the rda package. I use caret to tune over a grid and select an optimal value. I think I am then using the optimal selection for prediction. So there are two rounds of resampling with the first one taken care of by caret's train

Hi, I have been trying unsuccessfully to plot data using different colors based on a variable within a subset of an imported file. The file I am reading is about 20000 lines long and has a column (in the example called FILE) that contains approximately 100 unique entries. I would like to plot a subset of the data from the file and key the color from the FILE column, This is what my file looks like