search for: missclassif

Hello, I would like to know how to obtain the misclassification error when performing a boosting analisis with ADABAG package? With: > prop.table(Tesis.boostcv$confusion) I obtain the confusion matrix, but not the overall missclassification error. Thanks in advance, BSc. Cecilia Lezama Facultad de Ciencias - UDELAR Montevideo - Uruguay. [[alternative HTML version deleted]]

can you do Logistic regression in R, if so how do you do it and how do you test the fit of a model? -- View this message in context: http://n4.nabble.com/Logistic-regression-tp1059870p1059870.html Sent from the R help mailing list archive at Nabble.com.

I was wandering if anybody ever tried to compare the classification accuracy of nnet to other (rpart, tree, bagging) models. From what I know, there is no reason to expect a significant difference in classification accuracy between these models, yet in my particular case I get about 10% error rate for tree, rpart and bagging model and 80% error rate for nnet, applied to the same data. Thanks.

...by example from my choices and decide on my behalf (see column 4 in the attached file). That is: taking the output from step (1) above I can classify a few hundreds cases and then let the algorithm learn and classify future/additional data. I plan to regularly review such a classification, correct missclassifications and train the algorithm again with the objective to improve its ability to correctly classify the GA texts. Is my explanation clear enought? Can all the above be done within R? If so, is there any package/procedure I should be using? Thank you in advance for any suggestion you might have....

Dear mailing list, For two normal distributions, e.g: r1 =rnorm(20,5.2,2.1) r2 =rnorm(20,4.2,1.1) plot(density(r2), col="blue") lines(density(r1), col="red") Is there a way in R to compute/estimate the point(s) x where the density of the two distributions cross (ie where x has equal probability of belonging to either of the two distributions)? Many Thanks Eleni

So I have 2 sets of data - a training data set and a test data set. I've been doing the analysis on the training data set and then using predict and feeding the test data through that. There are 114 rows in the training data and 117 in the test data and 1024 columns in both. It's actually the same set of data split into two. The rows are made of 5 different numbers. They do represent

...nally, the estimation of bagging SVM is obtained by aggregating independently trained SVM?s in an appropriate aggregation technique.I've tried the program, can you correct them? I have the results of the program in accordance with the appropriate I expected because it turns out I do not get the missclassification Rate and aggregation. Can you help me?? thanks you so much for your attention best wishes, IUT TRI UTAMI Bogor Agricultural Institute, Indonesia -------------- next part -------------- #SINGLE SVM library(colorspace) library(rpart) library(e1071) library(MASS) dataset <- read.csv(&quot...