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  • Gomoku array-based AI-algorithm?

    - by Lasse V. Karlsen
    Way way back (think 20+ years) I encountered a Gomoku game source code in a magazine that I typed in for my computer and had a lot of fun with. The game was difficult to win against, but the core algorithm for the computer AI was really simply and didn't account for a lot of code. I wonder if anyone knows this algorithm and has some links to some source or theory about it. The things I remember was that it basically allocated an array that covered the entire board. Then, whenever I, or it, placed a piece, it would add a number of weights to all locations on the board that the piece would possibly impact. For instance (note that the weights are definitely wrong as I don't remember those): 1 1 1 2 2 2 3 3 3 444 1234X4321 3 3 3 2 2 2 1 1 1 Then it simply scanned the array for an open location with the lowest or highest value. Things I'm fuzzy on: Perhaps it had two arrays, one for me and one for itself and there was a min/max weighting? There might've been more to the algorithm, but at its core it was basically an array and weighted numbers Does this ring a bell with anyone at all? Anyone got anything that would help?

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  • Machine learning challenge: diagnosing program in java/groovy (datamining, machine learning)

    - by Registered User
    Hi All! I'm planning to develop program in Java which will provide diagnosis. The data set is divided into two parts one for training and the other for testing. My program should learn to classify from the training data (BTW which contain answer for 30 questions each in new column, each record in new line the last column will be diagnosis 0 or 1, in the testing part of data diagnosis column will be empty - data set contain about 1000 records) and then make predictions in testing part of data :/ I've never done anything similar so I'll appreciate any advice or information about solution to similar problem. I was thinking about Java Machine Learning Library or Java Data Mining Package but I'm not sure if it's right direction... ? and I'm still not sure how to tackle this challenge... Please advise. All the best!

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  • Boosting my GA with Neural Networks and/or Reinforcement Learning

    - by AlexT
    As I have mentioned in previous questions I am writing a maze solving application to help me learn about more theoretical CS subjects, after some trouble I've got a Genetic Algorithm working that can evolve a set of rules (handled by boolean values) in order to find a good solution through a maze. That being said, the GA alone is okay, but I'd like to beef it up with a Neural Network, even though I have no real working knowledge of Neural Networks (no formal theoretical CS education). After doing a bit of reading on the subject I found that a Neural Network could be used to train a genome in order to improve results. Let's say I have a genome (group of genes), such as 1 0 0 1 0 1 0 1 0 1 1 1 0 0... How could I use a Neural Network (I'm assuming MLP?) to train and improve my genome? In addition to this as I know nothing about Neural Networks I've been looking into implementing some form of Reinforcement Learning, using my maze matrix (2 dimensional array), although I'm a bit stuck on what the following algorithm wants from me: (from http://people.revoledu.com/kardi/tutorial/ReinforcementLearning/Q-Learning-Algorithm.htm) 1. Set parameter , and environment reward matrix R 2. Initialize matrix Q as zero matrix 3. For each episode: * Select random initial state * Do while not reach goal state o Select one among all possible actions for the current state o Using this possible action, consider to go to the next state o Get maximum Q value of this next state based on all possible actions o Compute o Set the next state as the current state End Do End For The big problem for me is implementing a reward matrix R and what a Q matrix exactly is, and getting the Q value. I use a multi-dimensional array for my maze and enum states for every move. How would this be used in a Q-Learning algorithm? If someone could help out by explaining what I would need to do to implement the following, preferably in Java although C# would be nice too, possibly with some source code examples it'd be appreciated.

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  • What is the best Battleship AI?

    - by John Gietzen
    Battleship! Back in 2003, (when I was 17,) I competed in a Battleship AI coding competition. Even though I lost that tournament, I had a lot of fun and learned a lot from it. Now, I would like to resurrect this competition, in the search of the best battleship AI. Here is the framework: Battleship.zip The winner will be awarded +450 reputation! The competition will be held starting on the 17th of November, 2009. No entries or edits later than zero-hour on the 17th will be accepted. (Central Standard Time) Submit your entries early, so you don't miss your opportunity! To keep this OBJECTIVE, please follow the spirit of the competition. Rules of the game: The game is be played on a 10x10 grid. Each competitor will place each of 5 ships (of lengths 2, 3, 3, 4, 5) on their grid. No ships may overlap, but they may be adjacent. The competitors then take turns firing single shots at their opponent. A variation on the game allows firing multiple shots per volley, one for each surviving ship. The opponent will notify the competitor if the shot sinks, hits, or misses. Game play ends when all of the ships of any one player are sunk. Rules of the competition: The spirit of the competition is to find the best Battleship algorithm. Anything that is deemed against the spirit of the competition will be grounds for disqualification. Interfering with an opponent is against the spirit of the competition. Multithreading may be used under the following restrictions: No more than one thread may be running while it is not your turn. (Though, any number of threads may be in a "Suspended" state). No thread may run at a priority other than "Normal". Given the above two restrictions, you will be guaranteed at least 3 dedicated CPU cores during your turn. A limit of 1 second of CPU time per game is allotted to each competitor on the primary thread. Running out of time results in losing the current game. Any unhandled exception will result in losing the current game. Network access and disk access is allowed, but you may find the time restrictions fairly prohibitive. However, a few set-up and tear-down methods have been added to alleviate the time strain. Code should be posted on stack overflow as an answer, or, if too large, linked. Max total size (un-compressed) of an entry is 1 MB. Officially, .Net 2.0 / 3.5 is the only framework requirement. Your entry must implement the IBattleshipOpponent interface. Scoring: Best 51 games out of 101 games is the winner of a match. All competitors will play matched against each other, round-robin style. The best half of the competitors will then play a double-elimination tournament to determine the winner. (Smallest power of two that is greater than or equal to half, actually.) I will be using the TournamentApi framework for the tournament. The results will be posted here. If you submit more than one entry, only your best-scoring entry is eligible for the double-elim. Good luck! Have fun! EDIT 1: Thanks to Freed, who has found an error in the Ship.IsValid function. It has been fixed. Please download the updated version of the framework. EDIT 2: Since there has been significant interest in persisting stats to disk and such, I have added a few non-timed set-up and tear-down events that should provide the required functionality. This is a semi-breaking change. That is to say: the interface has been modified to add functions, but no body is required for them. Please download the updated version of the framework. EDIT 3: Bug Fix 1: GameWon and GameLost were only getting called in the case of a time out. Bug Fix 2: If an engine was timing out every game, the competition would never end. Please download the updated version of the framework. EDIT 4: Results!

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  • Minimax algorithm: Cost/evaluation function?

    - by Dave
    Hi guys, A school project has me writing a Date game in C++ (example at http://www.cut-the-knot.org/Curriculum/Games/Date.shtml) where the computer player must implement a Minimax algorithm with alpha-beta pruning. Thus far, I understand what the goal is behind the algorithm in terms of maximizing potential gains while assuming the opponent will minify them. However, none of the resources I read helped me understand how to design the evaluation function the minimax bases all it's decisions on. All the examples have had arbitrary numbers assigned to the leaf nodes, however, I need to actually assign meaningful values to those nodes. Intuition tells me it'd be something like +1 for a win leaf node, and -1 for a loss, but how do intermediate nodes evaluate? Any help would be most appreciated.

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  • How to program a neural network for chess?

    - by marco92w
    Hello! I want to program a chess engine which learns to make good moves and win against other players. I've already coded a representation of the chess board and a function which outputs all possible moves. So I only need an evaluation function which says how good a given situation of the board is. Therefore, I would like to use an artificial neural network which should then evaluate a given position. The output should be a numerical value. The higher the value is, the better is the position for the white player. My approach is to build a network of 385 neurons: There are six unique chess pieces and 64 fields on the board. So for every field we take 6 neurons (1 for every piece). If there is a white piece, the input value is 1. If there is a black piece, the value is -1. And if there is no piece of that sort on that field, the value is 0. In addition to that there should be 1 neuron for the player to move. If it is White's turn, the input value is 1 and if it's Black's turn, the value is -1. I think that configuration of the neural network is quite good. But the main part is missing: How can I implement this neural network into a coding language (e.g. Delphi)? I think the weights for each neuron should be the same in the beginning. Depending on the result of a match, the weights should then be adjusted. But how? I think I should let 2 computer players (both using my engine) play against each other. If White wins, Black gets the feedback that its weights aren't good. So it would be great if you could help me implementing the neural network into a coding language (best would be Delphi, otherwise pseudo-code). Thanks in advance!

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  • My neural network gets "stuck" while training. Is this normal?

    - by Vivin Paliath
    I'm training a XOR neural network via back-propagation using stochastic gradient descent. The weights of the neural network are initialized to random values between -0.5 and 0.5. The neural network successfully trains itself around 80% of the time. However sometimes it gets "stuck" while backpropagating. By "stuck", I mean that I start seeing a decreasing rate of error correction. For example, during a successful training, the total error decreases rather quickly as the network learns, like so: ... ... Total error for this training set: 0.0010008071327708653 Total error for this training set: 0.001000750550254843 Total error for this training set: 0.001000693973929822 Total error for this training set: 0.0010006374037948094 Total error for this training set: 0.0010005808398488103 Total error for this training set: 0.0010005242820908169 Total error for this training set: 0.0010004677305198344 Total error for this training set: 0.0010004111851348654 Total error for this training set: 0.0010003546459349181 Total error for this training set: 0.0010002981129189812 Total error for this training set: 0.0010002415860860656 Total error for this training set: 0.0010001850654351723 Total error for this training set: 0.001000128550965301 Total error for this training set: 0.0010000720426754587 Total error for this training set: 0.0010000155405646494 Total error for this training set: 9.99959044631871E-4 Testing trained XOR neural network 0 XOR 0: 0.023956746649767453 0 XOR 1: 0.9736079194769579 1 XOR 0: 0.9735670067093437 1 XOR 1: 0.045068688874314006 However when it gets stuck, the total errors are decreasing, but it seems to be at a decreasing rate: ... ... Total error for this training set: 0.12325486644721295 Total error for this training set: 0.12325486642503929 Total error for this training set: 0.12325486640286581 Total error for this training set: 0.12325486638069229 Total error for this training set: 0.12325486635851894 Total error for this training set: 0.12325486633634561 Total error for this training set: 0.1232548663141723 Total error for this training set: 0.12325486629199914 Total error for this training set: 0.12325486626982587 Total error for this training set: 0.1232548662476525 Total error for this training set: 0.12325486622547954 Total error for this training set: 0.12325486620330656 Total error for this training set: 0.12325486618113349 Total error for this training set: 0.12325486615896045 Total error for this training set: 0.12325486613678775 Total error for this training set: 0.12325486611461482 Total error for this training set: 0.1232548660924418 Total error for this training set: 0.12325486607026936 Total error for this training set: 0.12325486604809655 Total error for this training set: 0.12325486602592373 Total error for this training set: 0.12325486600375107 Total error for this training set: 0.12325486598157878 Total error for this training set: 0.12325486595940628 Total error for this training set: 0.1232548659372337 Total error for this training set: 0.12325486591506139 Total error for this training set: 0.12325486589288918 Total error for this training set: 0.12325486587071677 Total error for this training set: 0.12325486584854453 While I was reading up on neural networks I came across a discussion on local minimas and global minimas and how neural networks don't really "know" which minima its supposed to be going towards. Is my network getting stuck in a local minima instead of a global minima?

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  • What problems have you solved using artificial neural networks?

    - by knorv
    I'd like to know about specific problems you - the SO reader - have solved using artificial neural network techniques and what libraries/frameworks you used if you didn't roll your own. Questions: What problems have you used artificial neural networks to solve? What libraries/frameworks did you use? I'm looking for first-hand experiences, so please do not answer unless you have that.

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  • Algorithm to generate numerical concept hierarchy

    - by Christophe Herreman
    I have a couple of numerical datasets that I need to create a concept hierarchy for. For now, I have been doing this manually by observing the data (and a corresponding linechart). Based on my intuition, I created some acceptable hierarchies. This seems like a task that can be automated. Does anyone know if there is an algorithm to generate a concept hierarchy for numerical data? To give an example, I have the following dataset: Bangladesh 521 Brazil 8295 Burma 446 China 3259 Congo 2952 Egypt 2162 Ethiopia 333 France 46037 Germany 44729 India 1017 Indonesia 2239 Iran 4600 Italy 38996 Japan 38457 Mexico 10200 Nigeria 1401 Pakistan 1022 Philippines 1845 Russia 11807 South Africa 5685 Thailand 4116 Turkey 10479 UK 43734 US 47440 Vietnam 1042 for which I created the following hierarchy: LOWEST ( < 1000) LOW (1000 - 2500) MEDIUM (2501 - 7500) HIGH (7501 - 30000) HIGHEST ( 30000)

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  • How can I extract similarities/patterns from a collection of binary strings?

    - by JohnIdol
    I have a collection of binary strings of given size encoding effective solutions to a given problem. By looking at them, I can spot obvious similarities and intuitively see patterns of symmetry and periodicity. Are there mathematical/algorithmic tools I can "feed" this set of strings to and get results that might give me an idea of what this set of strings have in common? By doing so I would be able to impose a structure (or at least favor some features over others) on candidate solutions in order to greatly reduce the search space, maximizing chances to find optimal solutions for my problem (I am using genetic algorithms as the search tool - but this is not pivotal to the question). Any pointers/approaches appreciated.

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  • Algorithm shortest path between all points

    - by Jeroen
    Hi, suppose I have 10 points. I know the distance between each point. I need to find the shortest possible route passing trough all points. I have tried a couple of algorithms (Dijkstra, Floyd Warshall,...) and the all give me the shortest path between start and end, but they don't make a route with all points on it. Permutations work fine, but they are to resource expensive. What algorithms can you advise me to look into for this problem? Or is there a documented way to do this with the above mentioned algorithms? Tnx Jeroen

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  • Neural Networks in C# using NeuronDotNet

    - by kingrichard2005
    Hello, I'm testing the NeuronDotNet library for a class assignment using C#. I have a very simple console application that I'm using to test some of the code snippets provided in the manual fro the library, the goal of the assignment is to teach the program how to distinguish between random points in a square which may or may not be within a circle that is also inside the square. So basically, which points inside the square are also inside the circle. Here is what I have so far: namespace _469_A7 { class Program { static void Main(string[] args) { //Initlaize the backpropogation network LinearLayer inputLayer = new LinearLayer(2); SigmoidLayer hiddenLayer = new SigmoidLayer(8); SigmoidLayer outputLayer = new SigmoidLayer(2); new BackpropagationConnector(inputLayer, hiddenLayer); new BackpropagationConnector(hiddenLayer, outputLayer); BackpropagationNetwork network = new BackpropagationNetwork(inputLayer, outputLayer); //Generate a training set for the ANN TrainingSet trainingSet = new TrainingSet(2, 2); //TEST: Generate random set of points and add to training set, //for testing purposes start with 10 samples; Point p; Program program = new Program(); //Used to access randdouble function Random rand = new Random(); for(int i = 0; i < 10; i++) { //These points will be within the circle radius Type A if(rand.NextDouble() > 0.5) { p = new Point(rand.NextDouble(), rand.NextDouble()); trainingSet.Add(new TrainingSample(new double[2] { p.getX(), p.getY() }, new double[2] { 1, 0 })); continue; } //These points will either be on the border or outside the circle Type B p = new Point(program.randdouble(1.0, 4.0), program.randdouble(1.0, 4.0)); trainingSet.Add(new TrainingSample(new double[2] { p.getX(), p.getY() }, new double[2] { 0, 1 })); } //Start network learning network.Learn(trainingSet, 100); //Stop network learning //network.StopLearning(); } //generates a psuedo-random double between min and max public double randdouble(double min, double max) { Random rand = new Random(); if (min > max) { return rand.NextDouble() * (min - max) + max; } else { return rand.NextDouble() * (max - min) + min; } } } //Class defines a point in X/Y coordinates public class Point { private double X; private double Y; public Point(double xVal, double yVal) { this.X = xVal; this.Y = yVal; } public double getX() { return X; } public double getY() { return Y; } } } This is basically all that I need, the only question I have is how to handle output?? More specifically, I need to output the value of the "step size" and the momentum, although it would be nice to output other information as well. Anyone with experience using NeuronDotNet, your input is appreciated.

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  • Face Recognition for classifying digital photos?

    - by Jeremy E
    I like to mess around with AI and wanted to try my hand at face recognition the first step is to find the faces in the photographs. How is this usually done? Do you use convolution of a sample image/images or statistics based methods? How do you find the bounding box for the face? My goal is to classify the pictures of my kids from all the digital photos. Thanks in advance.

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  • Nominal Attributes in LibSVM

    - by Chris S
    When creating a libsvm training file, how do you differentiate between a nominal attribute verses a numeric attribute? I'm trying to encode certain nominal attributes as integers, but I want to ensure libsvm doesn't misinterpret them as numeric values. Unfortunately, libsvm's site seems to have very little documentation. Pentaho's docs seem to imply libsvm makes this distinction, but I'm still not clear how it's made.

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  • Dont understand Python Method

    - by user836087
    I dont understand what is going on in the move method. I am taking the AI course from Udacity.com. The video location is: http://www.udacity.com/view#Course/cs373/CourseRev/apr2012/Unit/512001/Nugget/480015 Below is the code I dont get, its not working as shown in the video .. The answer I should be getting according to Udacity is [0, 0, 1, 0, 0] Here is what I get [] p=[0, 1, 0, 0, 0] def move(p, U): q = [] for i in range(len(p)): q.append(p[(i-U) % len(p)]) return q print move(p, 1)

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  • method for specialized pathfinding?

    - by rlbond
    I am working on a roguelike in my (very little) free time. Each level will basically be a few rectangular rooms connected together by paths. I want the paths between rooms to be natural-looking and windy, however. For example, I would not consider the following natural-looking: B X X X XX XX XX AXX I really want something more like this: B X XXXX X X X X AXXXXXXXX These paths must satisfy a few properties: I must be able to specify an area inside which they are bounded, I must be able to parameterize how windy and lengthy they are, The lines should not look like they started at one path and ended at the other. For example, the first example above looks as if it started at A and ended at B, because it basically changed directions repeatedly until it lined up with B and then just went straight there. I was hoping to use A*, but honestly I have no idea what my heuristic would be. I have also considered using a genetic algorithm, but I don't know how practical that method might end up. My question is, what is a good way to get the results I want? Please do not just specify a method like "A*" or "Dijkstra's algorithm," because I also need help with a good heuristic.

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  • Any good card game AI strategies?

    - by Mark
    What would be strategies for writing a good computer opponent for a card game? Most card games are games of incomplete information, so simply mapping out and traversing the game tree as one could do with a board game does not seem too promising. Maybe one could track what open cards are in the game (as soon as they are revealed) and assign probabilities to certain events (e.g. opponent still has 2 cards of clubs). Does anyone have experience with this? Links and directions greatly appreciated. Thanks! -Mark

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  • Finding minimum cut-sets between bounded subgraphs

    - by Tore
    If a game map is partitioned into subgraphs, how to minimize edges between subgraphs? I have a problem, Im trying to make A* searches through a grid based game like pacman or sokoban, but i need to find "enclosures". What do i mean by enclosures? subgraphs with as few cut edges as possible given a maximum size and minimum size for number of vertices for each subgraph that act as a soft constraints. Alternatively you could say i am looking to find bridges between subgraphs, but its generally the same problem. Given a game that looks like this, what i want to do is find enclosures so that i can properly find entrances to them and thus get a good heuristic for reaching vertices inside these enclosures. So what i want is to find these colored regions on any given map. My Motivation The reason for me bothering to do this and not just staying content with the performance of a simple manhattan distance heuristic is that an enclosure heuristic can give more optimal results and i would not have to actually do the A* to get some proper distance calculations and also for later adding competitive blocking of opponents within these enclosures when playing sokoban type games. Also the enclosure heuristic can be used for a minimax approach to finding goal vertices more properly. A possible solution to the problem is the Kernighan-Lin algorithm: function Kernighan-Lin(G(V,E)): determine a balanced initial partition of the nodes into sets A and B do A1 := A; B1 := B compute D values for all a in A1 and b in B1 for (i := 1 to |V|/2) find a[i] from A1 and b[i] from B1, such that g[i] = D[a[i]] + D[b[i]] - 2*c[a][b] is maximal move a[i] to B1 and b[i] to A1 remove a[i] and b[i] from further consideration in this pass update D values for the elements of A1 = A1 / a[i] and B1 = B1 / b[i] end for find k which maximizes g_max, the sum of g[1],...,g[k] if (g_max > 0) then Exchange a[1],a[2],...,a[k] with b[1],b[2],...,b[k] until (g_max <= 0) return G(V,E) My problem with this algorithm is its runtime at O(n^2 * lg(n)), i am thinking of limiting the nodes in A1 and B1 to the border of each subgraph to reduce the amount of work done. I also dont understand the c[a][b] cost in the algorithm, if a and b do not have an edge between them is the cost assumed to be 0 or infinity, or should i create an edge based on some heuristic. Do you know what c[a][b] is supposed to be when there is no edge between a and b? Do you think my problem is suitable to use a multi level problem? Why or why not? Do you have a good idea for how to reduce the work done with the kernighan-lin algorithm for my problem?

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  • What problems have you solved using genetic algorithms/genetic programming?

    - by knorv
    Genetic algorithms (GA) and genetic programming (GP) are interesting areas of research. I'd like to know about specific problems you - the SO reader - have solved using GA/GP and what libraries/frameworks you used if you didn't roll your own. Questions: What problems have you used GA/GP to solve? What libraries/frameworks did you use? I'm looking for first-hand experiences, so please do not answer unless you have that.

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  • Calculating Nearest Match to Mean/Stddev Pair With LibSVM

    - by Chris S
    I'm new to SVMs, and I'm trying to use the Python interface to libsvm to classify a sample containing a mean and stddev. However, I'm getting nonsensical results. Is this task inappropriate for SVMs or is there an error in my use of libsvm? Below is the simple Python script I'm using to test: #!/usr/bin/env python # Simple classifier test. # Adapted from the svm_test.py file included in the standard libsvm distribution. from collections import defaultdict from svm import * # Define our sparse data formatted training and testing sets. labels = [1,2,3,4] train = [ # key: 0=mean, 1=stddev {0:2.5,1:3.5}, {0:5,1:1.2}, {0:7,1:3.3}, {0:10.3,1:0.3}, ] problem = svm_problem(labels, train) test = [ ({0:3, 1:3.11},1), ({0:7.3,1:3.1},3), ({0:7,1:3.3},3), ({0:9.8,1:0.5},4), ] # Test classifiers. kernels = [LINEAR, POLY, RBF] kname = ['linear','polynomial','rbf'] correct = defaultdict(int) for kn,kt in zip(kname,kernels): print kt param = svm_parameter(kernel_type = kt, C=10, probability = 1) model = svm_model(problem, param) for test_sample,correct_label in test: pred_label, pred_probability = model.predict_probability(test_sample) correct[kn] += pred_label == correct_label # Show results. print '-'*80 print 'Accuracy:' for kn,correct_count in correct.iteritems(): print '\t',kn, '%.6f (%i of %i)' % (correct_count/float(len(test)), correct_count, len(test)) The domain seems fairly simple. I'd expect that if it's trained to know a mean of 2.5 means label 1, then when it sees a mean of 2.4, it should return label 1 as the most likely classification. However, each kernel has an accuracy of 0%. Why is this? On a side note, is there a way to hide all the verbose training output dumped by libsvm in the terminal? I've searched libsvm's docs and code, but I can't find any way to turn this off.

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  • Extracting pure content / text from HTML Pages by excluding navigation and chrome content

    - by Ankur Gupta
    Hi, I am crawling news websites and want to extract News Title, News Abstract (First Paragraph), etc I plugged into the webkit parser code to easily navigate webpage as a tree. To eliminate navigation and other non news content I take the text version of the article (minus the html tags, webkit provides api for the same). Then I run the diff algorithm comparing various article's text from same website this results in similar text being eliminated. This gives me content minus the common navigation content etc. Despite the above approach I am still getting quite some junk in my final text. This results in incorrect News Abstract being extracted. The error rate is 5 in 10 article i.e. 50%. Error as in Can you Suggest an alternative strategy for extraction of pure content, Would/Can learning Natural Language rocessing help in extracting correct abstract from these articles ? How would you approach the above problem ?. Are these any research papers on the same ?. Regards Ankur Gupta

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