similar to: ROC curve in randomSurvivalForest

Displaying 20 results from an estimated 10000 matches similar to: "ROC curve in randomSurvivalForest"

2010 Apr 30
0
ROC curve in randomForest
require(randomForest) rf.pred<-predict(fit, valid, type="prob") > rf.pred[1:20, ] 0 1 16 0.0000 1.0000 23 0.3158 0.6842 43 0.3030 0.6970 52 0.0886 0.9114 55 0.1216 0.8784 75 0.0920 0.9080 82 0.4332 0.5668 120 0.2302 0.7698 128 0.1336 0.8664 147 0.4272 0.5728 148 0.0490 0.9510 153 0.0556 0.9444 161 0.0760 0.9240 162 0.4564 0.5436 172 0.5148 0.4852 176 0.1730
2011 May 12
2
Can ROC be used as a metric for optimal model selection for randomForest?
Dear all, I am using the "caret" Package for predictors selection with a randomForest model. The following is the train function: rfFit<- train(x=trainRatios, y=trainClass, method="rf", importance = TRUE, do.trace = 100, keep.inbag = TRUE, tuneGrid = grid, trControl=bootControl, scale = TRUE, metric = "ROC") I wanted to use ROC as the metric for variable
2012 Jul 13
1
ROC curves with ROCR
Hi, I don't really understand how ROCR works. Here's another example with a randomforest model: I have the training dataset(bank_training) and testing dataset(bank_testing) and I ran a randomForest as below: bankrf<-randomForest(y~., bank_training, mtry=4, ntree=2, keep.forest=TRUE,importance=TRUE) bankrf.pred<-predict(bankrf, bank_testing)
2007 Sep 14
1
generate ROC curve using randomForest package
Hi, I am new here. I would like to compare the performance of the random forest model with support vector machine. Can anybody let me know how to generate a ROC curve for random forest model since there is no need to run the cross-validation. Thank you very much! TL _________________________________________________________________ [[replacing trailing spam]]
2017 Oct 16
1
ROC curve for each fold in one plot
Hi all, I have tried a 5 fold cross validation using caret package with random forest method on iris dataset as example. Then I need ROC curve for each fold: > set.seed(1) > train_control <- trainControl(method="cv", number=5,savePredictions = TRUE,classProbs = TRUE) > output <- train(Species~., data=iris, trControl=train_control, method="rf") >
2009 Nov 25
0
ROCR Issue: Averaging Across Multiple Classifier Runs in ROC Curve
Dear R-philes, I am having some trouble averaging across multiple runs of a classifier in an ROC Curve. I am using the ROCR package and the plot() method. First, I initialize a list with two elements where each element is a list of predictions and labels: vowel.ROC <- list(predictions=list(), labels=list()) For every run of the classifier, I append the scores and labels to their
2010 Jul 01
5
ROC curve in R
Hi, i have a fairly large amount of genomic data. I have created a dataframe which has "Reference" as one column and "Variation" as another. I want to plot a ROC curve based on these 2 columns. I have serached the R manual but I could not understand. Can anybody help me with the R code for plotting ROC curve. Thnx ashu6886 -- View this message in context:
2007 Jul 30
1
help with ROC curve
Hi I'm new to stats and R, so can you please help me or guide me building ROC curve in an elaborate way with codes I loaded ROCR package, but I'm not sure how to use it. Requirement To build ROC curve using only PSA(variable) alone of the original cohort against the ROC of the Model of the original cohort. It would be really great if you could help me with this. Thanks
2011 Oct 10
1
pmml for random forest & rules
Hi, I am having some trouble using R 2.13.1 for generating a pmml object of of class "c('randomForest.formula', 'randomForest')" I see that these methods are available: > methods(pmml) [1] pmml.coxph* pmml.hclust* pmml.itemsets* pmml.kmeans* pmml.ksvm* pmml.lm* pmml.multinom* pmml.nnet* pmml.rpart* [10] pmml.rsf* pmml.rules* pmml.survreg*
2005 Jul 19
1
ROC curve with survival data
Hi everyone, I am doing 5 years mortality predictive index score with survival analysis using a Cox proportional hazard model where I have a continous predictive variable and a right censored response which is the mortality, and the individuals were followed a maximum of 7 years. I'd like to asses the discrimination ability of survival analysis Cox model by computing a ROC curve and area
2009 Jul 27
0
ROC curve using epicalc (after logistic regression) (re-sent)
Dear R-help, I am resending as I believe I screwed up the e-mail address to R-help earlier. Sorry for my lack of attention to detail, and for any inconvenience. I have also sent the question to the package maintainer, as suggested in the posting guide. Regards, Cliff ---------- Forwarded message ---------- From: Clifford Long <gnolffilc at gmail.com> Date: Sun, Jul 26, 2009 at 8:46
2008 Feb 21
2
how to create ROC curve for 2 dimensional classifiers
Hi, I understand for 1 d classifiers, you can use ROCR package. Is there a package you can plot ROC curve for 2d classifiers? One of my colleagues asked me about this. I have been quite puzzled, conceptually, how you can do the ROC curve for 2d classifiers. Can someone share his/her knowledge or experience? Thanks in advance. -- Waverley @ Palo Alto
2012 Nov 22
3
ROC Curve: negative AUC
Hi all, does anyone know why the area under the curve (AUC) is negative? I'm using ROC function with a logistic regression, package Epi. First time it happens... Thanks a lot! Bruno -- View this message in context: http://r.789695.n4.nabble.com/ROC-Curve-negative-AUC-tp4650469.html Sent from the R help mailing list archive at Nabble.com.
2011 Apr 13
1
area under roc curve
Dear all, I want to measure the goodness of prediction of my linear model. That's why I was thinking about the area under roc curve. I'm trying the following, but I don't know how to avoid the error. Any help would be appreciated. library(ROCR) model.lm <- lm(log(outcome)~log(v1)+log(v2)+factor1) pred<-predict(model.lm) pred<-prediction(as.numeric(pred),
2009 Aug 21
1
ROC curve and gains/lift chart
What is the difference between ROC curve and gains/lift chart? how to do them in R? Thanks. -- View this message in context: http://www.nabble.com/ROC-curve-and-gains-lift-chart-tp25083979p25083979.html Sent from the R help mailing list archive at Nabble.com.
2005 Jan 11
1
Standard error for the area under a smoothed ROC curve?
Hello, I am making some use of ROC curve analysis. I find much help on the mailing list, and I have used the Area Under the Curve (AUC) functions from the ROC function in the bioconductor project... http://www.bioconductor.org/repository/release1.5/package/Source/ ROC_1.0.13.tar.gz However, I read here... http://www.medcalc.be/manual/mpage06-13b.php "The 95% confidence interval for
2011 Mar 13
1
use of ROCR package (ROC curve / AUC value) in a specific case versus integral calculation
Hello, I would like to use the ROCR package to draw ROC curves and compute AUC values. However, in the specific context of my application, the true positive rates and false positive rates are already provided by some upstream method. Of course, I can draw a ROC plot with the following command : plot(x=FPrate, y=TPrate, "o", xlab="false positive rate", ylab="true
2011 Mar 31
0
pROC 1.4.3: compare two ROC curves in R
Dear R users, pROC is a package to compare, visualize, and smooth receiver operating characteristic (ROC) curves. The package provides the following features: * Partial or full area under the curve (AUC) computation * Comparison of two ROC curves (curves and AUC) * Calculating and plotting confidence intervals * Smoothing of the ROC curve * Coordinates extraction ('coords' function).
2011 Mar 31
0
pROC 1.4.3: compare two ROC curves in R
Dear R users, pROC is a package to compare, visualize, and smooth receiver operating characteristic (ROC) curves. The package provides the following features: * Partial or full area under the curve (AUC) computation * Comparison of two ROC curves (curves and AUC) * Calculating and plotting confidence intervals * Smoothing of the ROC curve * Coordinates extraction ('coords' function).
2008 Oct 31
4
how to compute a roc curve
Hi, I'm trying to set up a prediction software, now i testing the performance of my method, so i need to calculate a ROC curve, specially auc, cut-off, sens and spec, i just looking at ROCH package, but it's a mass for me, i'm not a math guy and I'm getting lost Could any of you recommend me an easy-to-use package to do this task? i just have a list of positive/negative samples