search for: decisions

Hello, this question is a bit out of the blue. I am a big R fan and user and in my new job I do some decision modeling (mostly health economics). For that decision trees are often used (I guess the most classic example is the investment decision A, B, and C with different probabilities, what is the expected payoff). We use a specialized software called TreeAge that some might know. The basic

A client has inquired about producing a decision tree from data which could include: - ID of brand purchased - Importance ratings (1-10 scale) for a number of relevant attributes (price, strength, recommended by a friend, etc.) In other words, a rating of how important each attribute is in the decision as to which brand to purchase. I've just run a test decision tree using the closest thing

Ok is there a way to do it with decision tree? I just need to make the decision rules. Perhaps I can pick one of the trees used with Random Forrest. I am somewhat familiar already with Random Forrest with respective to bagging and feature sampling and getting the mode from the leaf nodes and it being an ensemble technique of many trees. I am just working from the perspective that I need

...work hard on LLVM but never ended up owning a piece of code and would be telling that committing a lof of patches is somehow better than a few well done and life changing ones. Maybe we do need to start a parallel discussion on how would this technical committee would look like, so we can take such decisions while still being representative with more ease in the future. But none of that is fast enough, I think. The only easy solution I can see right now, is for Chris Lattner to decide, based on both the survey and the BoF. I personally trust Chris to take a decision that will be best for the community...

...t; > > Current compilers have pipeline structure in which data from one > > phase is > > passed to the following one. But these compilation phases can > > interfere in > > unpredictable way so compilers use conservative heuristics on which > > they > > make decisions during the compilation process. Because of > > unpredictability > > of these interferences, compilers sometimes make decisions which can > > degrade > > code quality. Iterative compilation could partially resolve these > > problems > > by allowing compiler to exp...

This patch: * adds a C-based security policy translation tool to Xen (secpol_xml2bin) and removes the current Java security policy translator (Java dependencies). The C-based tool integrates into the Xen source tree build and install (using gnome libxml2 for XML parsing). See install.txt. * introduces security labels and related tools. Users can now use semantic-rich label names to put

...pecially those related to integration of the framework into Clang/LLVM. Current compilers have pipeline structure in which data from one phase is passed to the following one. But these compilation phases can interfere in unpredictable way so compilers use conservative heuristics on which they make decisions during the compilation process. Because of unpredictability of these interferences, compilers sometimes make decisions which can degrade code quality. Iterative compilation could partially resolve these problems by allowing compiler to explore some alternative decisions, generate code for these new...

On 2015-02-10, Always Learning <centos at u64.u22.net> wrote: > > My decisions are based on what I know. Those decisions can be called > "informed decisions". Calling them "informed decisions" doesn't automatically make them informed decisions. --keith -- kkeller at wombat.san-francisco.ca.us

Hi Everyone, Numerous people have been bringing up challenges with consensus driven decision making in the LLVM community. After considering this and seeing the frustrations it is causing many people, I think we should make a formal process change to help improve decision making going forward. Here is the outline of the draft proposal

Hi Experts, I am new to R, using decision tree model for getting segmentation rules. A) Using behavioural data (attributes defining customer behaviour, ( example balances, number of accounts etc.) 1. Clustering: Cluster behavioural data to suitable number of clusters 2. Decision Tree: Using rpart classification tree for generating rules for segmentation using cluster number(cluster id) as target

Hi I'm trying to get the top decision rules from a decision tree. Eventually I will like to do this with R and Random Forrest. There has to be a way to output the decsion rules of each leaf node in an easily readable way. I am looking at the randomforrest and rpart packages and I dont see anything yet. Mike [[alternative HTML version deleted]]

...ow that you have all the best intentions here, so please take this in the spirit of productive conversation that is intended. "Meritocracy" always makes me feel uncomfortable. Many many people interpret that to mean those with the most experience/social capital are best equipped to make decisions. Not only is that not always true, it leads to an organization with structural barriers to newcomers, those with different/less common backgrounds and dissenting views. I definitely do not want to go for "meritocracy." > Hoewever, I'd strongly advise against a simple voting syst...

Hi, I am somewhat new to R so this question may be foolish, but is it possible to add decision trees into a list, array or vector in R? I am trying to build a collection (ensemble) of decision trees. Every time a new instance arrive I need to get the prediction of each decision tree. I have tried to add a decision tree into a variable but without luck. Is a special package needed perhaps? This

...be a long design discussion :) > > Current compilers have pipeline structure in which data from one > phase is > passed to the following one. But these compilation phases can > interfere in > unpredictable way so compilers use conservative heuristics on which > they > make decisions during the compilation process. Because of > unpredictability > of these interferences, compilers sometimes make decisions which can > degrade > code quality. Iterative compilation could partially resolve these > problems > by allowing compiler to explore some alternative decision...

...have pipeline structure in which data from one > > > phase is > > > passed to the following one. But these compilation phases can > > > interfere in > > > unpredictable way so compilers use conservative heuristics on which > > > they > > > make decisions during the compilation process. Because of > > > unpredictability > > > of these interferences, compilers sometimes make decisions which can > > > degrade > > > code quality. Iterative compilation could partially resolve these > > > problems > > &g...

On Tue, February 10, 2015 4:04 pm, Warren Young wrote: >> On Feb 9, 2015, at 12:12 PM, John R Pierce <pierce at hogranch.com> wrote: >> >> On 2/9/2015 11:06 AM, Always Learning wrote: >>> The third item was a 16.1 MB PDF of 1,344 pages. A quick scan of the >>> PDF >>> shows every page appears to be readable. 11 pages devoted to BASH. >>>

Dear mailinglist members, I have the following problem: I run a decision tree using the rpart function and, afterwords, I try to find to which leaf node a new register (not used to build the decision tree) belongs to. I will try to explain better: rpart.tree <- rpart(target.value ~., data) leaf.node <- new.function(rpart.tree, new.register) The new register has all the explanatory values

Have anybody used Decision Tree in Python or C++? (or written their own decision tree implementation in Python or C++)? My goal is to run decision tree on 8 million obs as training set and score 7 million in test set. I am testing 'rpart' package on a 64-bit-Linux + 64-bit-R environment. But it seems that rpart is either not stable or running out of memory very quickly. (Is it

Nope. Random forests are not decision trees -- they are ensembles (forests) of trees. You need to go back and read up on them so you understand how they work. The Hastie/Tibshirani/Friedman "The Elements of Statistical Learning" has a nice explanation, but I'm sure there are lots of good web resources, too. Cheers, Bert Bert Gunter "The trouble with having an open mind is

...extensions needed for CFI and make sure they can fit into this model. Thanks, Teresa Background ---------------- Recent patch D18945/r266125 ([ThinLTO] Only compute imports for current module in FunctionImport pass) triggered a discussion (mostly over IRC) on how best to determine import/export decisions in distributed back end compiles. Import and export decisions are made by traversing the combined index. The actual importing happens in the FunctionImporter class, which is passed the set of values to import. The importer class is either invoked directly on each backend compile, which happens in...