similar to: U32 classifier filter

Hi Patrick ! I find simple error in extensions/libipt_ROUTE.c line 24 and 127 -- change NETFILTER_VERSION to IPTABLES_VERSION extensions/libipt_IMQ.c line 18 and 87 -- change NETFILTER_VERSION to IPTABLES_VERSION (iptables-20020618) ----------------------------------- mailto:alexey_talikov@texlab.com.uz BR Alexey Talikov FORTEK -----------------------------------

ingress can be used to control the incoming packet, such as: tc qdisc add dev eth0 handle ffff: ingress tc filter add dev eth0 parent ffff: protocol ip prio 5 u32 match ip src 172.16.1.11 police rate 10kbit burst 10k drop flowid :1 tc filter add dev eth0 parent ffff: protocol ip prio 5 u32 match ip src 172.16.1.22 police rate 10kbit burst 10k drop flowid :2 first ,I do not sure these method can

Hello everybody, I have tried several iptables versions (from 1.2.4 to 1.2.6a) to mark outgoing packets (change the DSCP field) with no success. #iptables -A OUTPUT -t mangle -d 10.0.0.3 -j DSCP --set-dscp 0x2 iptables v1.2.6a: unknown arg ''--set-dscp'' TOS target is working fine, but I want to create different codes for EF and AF classes in a diffserv

Hello, I have made every effort learning QoS. I chose HTB and wrote a script (attached to the message). The problem is error messages in syslog. They appear on heavy load. It looks like: Jun 12 23:00:04 server kernel: KERNEL: assertion (delay > 0 && delay < 5000000) failed at sch_htb.c(411) Jun 12 23:00:41 server last message repeated 12 times Jun 12 23:01:42 server last message

Le jeudi 09 f?vrier 2012 ? 15:31 +0200, Kari Ruohonen a ?crit : > Hi, > I am trying to replicate a training of AttributeSelectedClassifier with > CFsSubsetEval, BestFirst and NaiveBayes that I have initially done with > Weka. Now, I am trying to use RWeka in R. > > I have a problem of passing arguments to the CfsSubsetEval, BestFirst > and NaiveBayes. I have first created an

Hello all, As I have promised I am sending my QoS rules. This now works fine with u32 classifier (and parent 1:0 that I could not understand why it did not worked well before). Att, Nataniel Klug ------------------------ #!/bin/sh #------ # Script de QoS Cyber Nett #------ # Nataniel Klug # suporte@cnett.com.br #------ TC="/sbin/tc" IPT="/usr/local/sbin/iptables"

Hello, I just compiled a new kernel.iptable/iproute2 to fresh up my router. There is a little problem... The fw classifier does not work in tc. I read some note found in the source of iproute2 and it says: "* To use "fw" classifier you will need ipfwchains patch." I can''t find this patch. Do you have it? Is there any other way to implement the "fw"

Hi, Currently I testing the packets that contain built-in features for classification. Actually I looked packages such as: e1071, Klar, Caret, CORElearn. However, from what I noticed when building a naive Bayesian classifier, that they package use of the finite mixture model to estimate P (x | C) and using a normal distribution. In my research I use binary data and I want modeled P (x | C), eg the

Dear All, I'm currently doing a project about unsupervised learning, and I'll be using R to analyse a few network traffic datasets downloaded off Andrew Moore's website (http://www.cl.cam.ac.uk/Research/SRG/netos/nprobe/data/papers/sigmetrics/index.html). Could anyone shed some light on how to build a classifier from the training set A, and then use a validation set B to assess the

Hi, I have a bunch of data points x from two classes A & B, and I'm creating a classifier. So I have a function f(x) which estimates the probability that x is in class A. (I have an equal number of examples of each, so p(class) = 0.5.) One way of seeing how well this does is to compute the error rate on the test set, i.e. if f(x)>0.5 call it A, and see how many times I

Dear R users, we are glad to announce the release of our new R package ROCR, for visualizing the performance of scoring classifiers (available on CRAN). We hope that the package might be useful for those of you working on classification problems. For details, see the package description below, or the ROCR website: http://rocr.bioinf.mpi-sb.mpg.de. You can get a short overview by typing

Dear R users, we are glad to announce the release of our new R package ROCR, for visualizing the performance of scoring classifiers (available on CRAN). We hope that the package might be useful for those of you working on classification problems. For details, see the package description below, or the ROCR website: http://rocr.bioinf.mpi-sb.mpg.de. You can get a short overview by typing

Hi I am trying to use randomForest for classification. I am using this code: > set.seed(71) > rf.model <- randomForest(similarity ~ ., data=set1[1:100,], importance=TRUE, proximity=TRUE) Warning message: The response has five or fewer unique values. Are you sure you want to do regression? in: randomForest.default(m, y, ...) > rf.model Call: randomForest(x = similarity ~ .,

Hi, Apology for this question being off the topic (OT) of R, though I expect this list might be the best place on the net to ask this question. In brief, the question is: what classification algorithm can one use if the features are histograms? I have a classification problem, and believe that histograms of the distribution of some values may be the best "feature" to use. To

Hi, Everyone, I just installed R-2.7.2 on my computer and then installed package RWeka, version 0.3-13. I noticed that when using command "evaluate_Weka_Classifier", with parameter "newdata=", it still evaluated on training data. Does anyone else noticed this? My older version of R-2.6.1 with RWeka 0.3-9 worked fine on the same computer. Bin

Hi everyone, I have a test set with more than 1000 cases, when I use evaluate_Weka_classifier(RWeka)to evaluate my classifier on this test set, the output shows me the result of only 83 cases. I do have missing values in predictors, so I tried na.acton=na.pass, but it dosen't help. Now I confused, why RWeka ignore so many cases in my test set? Is there any setting I didn't notice in

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

Hi, I have a small doubt regarding naive Bayes. I am able to classify the data's properly but i am just stuck up with how to get the probability values for naive bayes. In the case of SVM we have "attr" function that helps in displaying the probability values. Is there any function similar to "attr" in naive Bayes that can be used for displaying the attribute values. my

Hi everyone, I have trouble to use RWeka, I tried: (w=weather dataset, all preditors are nominal) > m<-J48(play~., data=w) > e<-evaluate_Weka_classifier(m,cost = matrix(c(0,2,1,0), + ncol = 2),numFolds = 10, complexity = TRUE,seed = 123, + class = TRUE) it gives me exactly what I want, but when I tried the same classifier on the other published data: (iris dataset has all numeric

Hi all! On http://lartc.org/howto/lartc.adv-filter.html I read that a classifiers available bases the decision on how the firewall has marked the packet and on http://lartc.org/howto/lartc.qdisc.filters.html the following example: "tc filter add dev eth1 protocol ip parent 1:0 prio 1 handle 6 fw flowid 1:1" "iptables -A PREROUTING -t mangle -i eth0 -j MARK --set-mark 6" My