I find useful groups.google.com/group/comp.lang.prolog/topics cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/ google.com/Top/Computers/Programming/Languages/Prolog/Implementations/ allisons.org/ll/Logic/Prolog/Examples/ prolog.info/ Maybe there are else useful links? Please share it :-) ...
Hi, I'm not sure whats the best algorithm to use for the classification of relationships in words. For example in the case of a sentence such as "The yellow sun" there is a relationship between yellow and sun. THe machine learning techniques I have considered so far are Baynesian Statistics, Rough Sets, Fuzzy Logic, Hidden markov model ...
Hi All, How can I measure the speed of code written in Java? I planning to develop software which will solve Sudoku using all presently available AI and ML algorithms and compare time against simple brute-force method. I need to measure time of each algorithm, I would like to ask for suggestions on what is the best way of doing that? ...
Hello all, I want to classify using libsvm. I have 9 training sets , each set has 144000 labelled instances , each instance having a variable number of features. It is taking about 12 hours to train one set ( ./svm-train with probability estimates ). As i dont have much time , I would like to run more than one set at a time. I'm not su...
Hello all , I am using libsvm for binary classification.. I wanted to try grid.py , as it is said to improve results.. I ran this script for five files in separate terminals , and the script has been running for more than 12 hours.. this is the state of my 5 terminals now : [root@localhost tools]# python grid.py sarts_nonarts_feat.txt...
I have trained xor neural network in Matlab and got these weights: iw: [-2.162 2.1706; 2.1565 -2.1688] lw: [-3.9174 -3.9183] b{1} [2.001; 2.0033] b{2} [3.8093] Just from curiosity I have tried to write MATLAB code which computes the output of this network (2 neurons in hidden layer, and 1 in output, TANSIG activation function). C...
Hi, I have an application that needs to discriminate between good HTTP GET requests and bad. For example: http://somesite.com?passes=dodgy+parameter # BAD http://anothersite.com?passes=a+good+parameter # GOOD My system can make a binary decision about whether or not a URL is good or bad - but ideally I would...
I want to detect one kind of object such as person in the picture, who can tell me how to training a kind of people classifier for use,so we can use the classifier to detect people in any picture. ...
This is a community wiki which aims to provide a good design for a machine learning/artificial intelligence framework (ML/AI framework). Please contribute to the design of a language-agnostic framework which would allow multiple ML/AI algorithms to be plugged into a single framework which: runs the algorithms with a user-specified d...
I have a simple photograph that may or may not include a logo image. I'm trying to identify whether a picture includes the logo shape or not. The logo (rectangular shape with a few extra features) could be of various sizes and could have multiple occurrences. I'd like to use Computer Vision techniques to identify the location of these...
Is there anyway to use the examples for the "My Media" Microsoft research project? My Media is a "dynamic personalization and recommendation software framework toolkit" ( http://www.mymediaproject.org ), but out of the box it doesn't provide a sample database (only a LINQ-to-SQL .dbml schema), I don't believe it will be easy to re-create...
We need to decide between Support Vector Machines and Fast Artificial Neural Network for some text processing project. It includes Contextual Spelling Correction and then tagging the text to certain phrases and their synonyms. Which will be the right approach? Or is there an alternate to both of these... Something more appropriate than...
Dear Everyone, I Hear that google uses up to 7-grams for their semantic-similarity comparison. I am interested in finding words that are similar in context (i.e. cat and dog) and I was wondering how do I compute the similarity of two words on a n-gram model given that n > 2. So basically given a text, like "hello my name is blah blah. I...
I've been searching the net for ~3 hours but I couldn't find a solution yet. I want to give a precomputed kernel to libsvm and classify a dataset, but: How can I generate a precomputed kernel? (for example, what is the basic precomputed kernel for Iris data?) In the libsvm documentation, it is stated that: For precomputed kernels, the...
I'm not sure what's the appropriate terminology here, but I'd like to have an application running passively that is ready to accept commands without having to reinitialize the whole thing. The precise application is a machine learning system written in Python that takes a somewhat long time to train a classifier or to load a cached clas...
Hi, I'm a newbie to the world of ANN. I'm aware of the Gradient Desecent Rule and the Backpropagation Theorem. What I don't get is , when is using a bias important? For example, when mapping the AND function, when i use 2 inputs and 1 output, it does not give the correct weights, however , when i use 3 inputs(1 of which is a bias), it g...
A lot univariate decision tree learner implementations (C4.5 etc) do exist, but does actually someone know multivariate decision tree learner algorithms? ...
Assume I have a set of weighted samples, where each samples has a corresponding weight between 0 and 1. I'd like to estimate the parameters of a gaussian mixture distribution that is biased towards the samples with higher weight. In the usual non-weighted case gaussian mixture estimation is done via the EM algorithm. Does anyone know an ...
i'm working on a project and need your ideas, advices. First of all, let me tell my problem. There is power button and some other keys of a machine and there is only one user has authentication to use this machine.There are no other authentication methods, the machine is in public area in a company. the machine is working with the co...
I'm trying to classify an example, which contains discrete and continuous features. Also, the example represents sparse data, so even though the system may have been trained on 100 features, the example may only have 12. What would be the best classifier algorithm to use to accomplish this? I've been looking at Bayes, Maxent, Decision T...