similar to: External Node Classifiers

Hi, I just added an external classifier script, and things are not working as I expected to. Trying to read documentation about ext.nodes and searching the archives I couldn''t come up with any useful results. My classifier script outputs: --- YAML --- classes: - geodns::production::backend environment: production name: z01-06-02 parameters: puppet_server:

All, I am sure this is just something I am doing wrong, but I am trying to implement a node classifier (shell script) to have my nodes inherit the proper classes. However, when I run it I am not getting any classes except those that are defined in default. Rather than going into detail showing all of my configurations right off the bat, I have a question: I just stood up a

Hi, I am using some classifiers in RWeka packages and met a couple problems. (1) J48 implements C45 classifier, the C45 should be able to handle missing values in both training set and test set. But I found the J48 classifier can not be evaluated on test set with missing values--it just ignore them. (2) The ensemble classifiers in RWeka such as bagging and boosting: there is a

Hi, I am using some classifiers in RWeka packages and met a couple problems. (1) J48 implements C45 classifier, the C45 should be able to handle missing values in both training set and test set. But I found the J48 classifier can not be evaluated on test set with missing values--it just ignore them. (2) The ensemble classifiers in RWeka such as bagging and boosting: there is a

Hello, I have some trouble in achieving the desired parametrisation for the weka classifier functions, using the package RWeka. The problem is, that the functions result=classifier(formula, data, subset, na.action, control = Weka_control(mycontrol)) do not seem to be manipulated by the mycontrol- arguments Perhaps this should be resepected via the handlers- argument , but the

I am using machine learning for one researching. I am using some classifiers with 5-fold CV . I would like to know how it is possible to extract the accuracy, for example, for KNN,neural networks and J48, for each one of 5-fold because when I apply CV to my classifier, I obtain the "mean accuracy" of 5-fold but each accuracy/error of each fold is not returned. Any help is welcome and

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

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

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 Krishna, 1) If you want to classify according to MAC address, you could use iptables to mark the packet (using MARK target), but just source MAC is available for now. 2) Usually tc just could classify by fields of IP layer and its sublayer, so I think classify by ethertype is unavailable. 3) VLAN tag belongs to MAC layer! I''m not sure how to QoS for VLAN, can anybody give some

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

Hi, I am a newbie working on tc tool, i want to know whether we have the following classifiers available (1) source MAC address. (2) destination MAC address. (3) IEEE 802.1D user priority. (4) Ethertype (IEEE 802.3, 1998 Length/Type Field). Can any one help me in finding the help for the above classifiers. Thanks in advance Krishna Chaitanya

Hello! Does anyone know how to apply bagging for SVM? ( for example) I am using adabag package to execute bagging but this method, "bagging", works with classification trees. I would like to apply my bagging to other classifiers as SVM,RNA or KNN. Has anyone do it? Thanks!! [[alternative HTML version deleted]]

I've been trying to get some linear classifiers (LiblineaR, kernlab, e1071) to work with a sparse matrix of feature data. In the case of LiblineaR and kernlab, it seems I have to coerce my data into a dense matrix in order to train a model. I've done a number of searches, read through the manuals and vignettes, but I can't seem to see how to use either of these packages with sparse

Hello! I am glad to announce a patch for u32 to allow matches on nfmark. The patch is non intrusive (few lines). Why I did this? Because fw classifier cannot be used together with u32. For example, now, you cannot match a mark of 0x90 and a destination port of 80. I know you can do it with iptables to do the marking, but if you use Jamal actions to apply mark to policed packets, you need

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, 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

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 All, I''m not convinced I have my tcrules correctly setup and looking at the counters in the mangle table''s tcpost doesn''t really help much as I can''t tell what is the final match. Is there a way to match packets in iptables based on the classifier? i.e. so I can LOG packets classified with 1:18 for example. I can''t see anything in iptables, except

Hi to all, I'm new to this forum and new to R. I have to build a tree classifier that has boolean values as response. When I build the tree with: echoknn.tree <- tree(class ~ ., data=echoknn.train) where "class" is a coloumn of my dataset (echoknn.train) of boolean values, the result is a tree where leaf nodes are numbers in the range [0,1]; but this isn't the result that I