The genetic-algorithms tag has no wiki summary.
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Requirements for Evaluation function in evolutionary algorithms
For a publication I'm looking for references for generic requirements of evaluation/fitness functions in evolutionary (more specifically genetic) algorithms.
I could come up with some requirements ...
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Finding the similarity between two functions
I am a first-year grad student in Computer Science, and I need some help with a problem that I think is statistically oriented. I have taken a statistics course, but it was abysmal and I haven't had ...
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Backpropagation vs Genetic Algorithm for Neural Network training
I've read a few papers discussing pros and cons of each method, some arguing that GA doesn't give any improvement in finding the optimal solution while others show that it is more effective. It seems ...
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How to statistically compare two algorithms across three datasets in feature selection and classification?
Problem background: As part of my research, I have written two algorithms that can select a set of features from a data set (gene expression data from cancer patients). These features are then tested ...
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Citation for Continuous Space Hill Climbing Algorithm pseudocode on Wikipedia?
Can anyone provide a reference for the Continuous Space Hill Climbing Algorithm pseudocode in the Wikipedia article on Hill Climbing? The Russell and Norvig text is cited, but they only provide the ...
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1answer
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How to chose optimal number of lags and inputs?
I'm using Genetic Algorithms to do inputs selection in a time series problem. The issue is that the number of possible inputs is very large (100 possible inputs + inputs' lags) and I don't know a ...
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1answer
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How to compare different heuristics over a large number of test instances
I have 3 different heuristics (H1, H2, H3) that are variation of genetic algorithms combined with some other techniques.
The problem that I try to solve is The problem to minimize energy costs for ...
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216 views
How to decide whether to reuse old code or reinvent the wheel?
For a long time now, I have been thinking about working with neural networks and genetic algorithms. I have never been able to decide whether it makes sense to start writing my own code, or to reuse ...
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113 views
Framework for Symbolic Classification
Please advise good framework for symbolic classification. I am currently using GPTIPS for that but I belive there are better options.
What I am trying to do is following:
for set of features of my ...
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Genetic algorithms, genetic programming or machine learning algorithms for solving this problem
I have a problem that consists of finding the optimal solution based on the following criteria:
Logic for identifying that event A has occurred (i.e. "find" logic that most accurately categorises an ...
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1answer
457 views
How to avoid overfitting when using crossvalidation within Genetic Algorithms
This is a long set-up, but the pure intellectual challenge will make it worthwhile I promise ;-)
I have marketing data where there is a treatment and a control (i.e a customer gets no treatment). The ...
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How to perform genetic-algorithm variable selection in R for SVM input variables?
I'm using the kernlab package in R to build an SVM for classifying some data.
The SVM is working nicely in that it provides 'predictions' of a decent accuracy, however my list of input variables is ...
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Benefits of using genetic algorithm
Can anyone explain to me the benefits of the genetic algorithm compared to other traditional search and optimization methods?
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What language to use for genetic programming
As part of an assignment I'll have to write a genetic programming algorithm that does prediction of atmospheric pollutant levels. Since I have no experience, can anyone point me pointers to ...
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2answers
250 views
Convergence of a genetic algorithm
Does anyone know of any method for deciding when a genetic algorithm is done? In MCMC (e.g, BUGS), several chains are started at different, random points. When they all look the same, it is done. Has ...
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1answer
70 views
On what tasks does neuroevolution outperform basic application of neural networks or genetic algorithms?
There has been a recent interest in combining genetic algorithms and neural networks into a general neuroevolution framework. The basic idea, is that your genetic algorithm is evolving the parameters ...
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183 views
Curve fitting multivariate data for maximal correlation with univariate data?
I have multivariate time series data of the EURUSD financial vehicle. In this data each variable represents a different metric. There are ~200,000 rows and ~20 variables.
There are no NULL values for ...
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1answer
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Correct way of testing machine learning against random data
I am using a genetic algorithm to search a very complex hypothesis space. Now I want to estimate how much overfitting I can expect in the final resulting hypothesis. The final model will be used for ...
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Feature construction in R
I am wondering if there are any algorithms (perhaps genetic algorithms) in R for feature construction (deriving candidate predictors from existing predictors)? I am thinking of a routine to test ...
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2answers
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Is there an R optimization package that can handle integer constraints and non-linear objective functions?
I am looking for an optimization routine that can optimize a non-linear objective function with integer constraints. NuOPT for S-Plus, CPLEX, or Matlab include powerful optimization packages for these ...
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Genetic algorithm for parameter estimation
I am a bit confused about parameter estimation using evolutionary methods and their ability to do such a job. Since I am not that pro in stat I am describing my problem with giving an example.
Given ...
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Random number generation
Generating n random variables whose summation will be 1. [I got the answer.]
EDIT
On genetic algorithm, we have to maintain population. Say, I have two individuals a and b. Every individual consists ...
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2answers
509 views
How to choose between learning algorithms
I need to implement a program that will classify records into 2 categories (true/false) based on some training data, and I was wondering at which algorithm/methodology I should be looking at. There ...
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5answers
868 views
How to check if modified genetic algorithm is significantly better than the original?
My question deals with how to be able to assert that an "improved"
evolutionary algorithm is indeed improved (at least from a statistic
point of view) and not just random luck (a concern given the
...
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1answer
274 views
Nonlinear models which are hard to estimate
Genetic algorithms are avoided in econometry literature as often as possible, but still sometimes they are inevitable. The question is: Which well known models are the most difficult to estimate using ...
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Are there any recommended approaches for analysing data from genetic algorithms?
After running a study based on interactive genetic algorithms, I have a univariate data file containing multiple participants each doing multiple generations (blocks) of multiple trials.
Is there an ...
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1answer
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Rating how closely one graph models another
I'm using a genetic algorithm to generate a string that produces certain results I map into a line/bar graph. I'm trying to rate how closely the results produced by the genetic string compares to a ...
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Comparing two genetic algorithms
I have two implementations of a genetic algorithm which are supposed to behave equivalently. However due to technical restrictions which cannot be resolved their output is not exactly the same, given ...
