# Tagged Questions

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### GA or ANN, and suggestions

I am working to approximate, to extrapolate rather, values of a function from a few known values. Here is what I have: Less than 100 known I/O pairs. A monotonously positive correlation.en Something ...
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### Reference in Genetic Algorithm Neural network

I am planning to work on my thesis with genetic algorithm neural network (GANN), since that is a modern statistical technique instead of by using discriminant analysis which is a traditional ...
119 views

### Overcoming small dataset anomalies in genetic algorithm

So I am currently making my 6th version of a model designed to predict the likelihood of of a particular medical condition based on a multifactorial genetic markers and I really would appreciate some ...
44 views

### Design fitness function for polynomial approximation

I'm trying to apply a polynomial approximation for a given function (via Genetic Algorithms), and so far the results are not so good: ...
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### How to deal with chromosomes of different lengths genes in genetic algorithm?

If I have 6 products ($x$) and 11 manufacturers ($y$) some products manufactured by some of these manufacturers; ($x,y$) may equal none or any other value. For each combination of $x$ and $y$ there ...
85 views

### Expected value of item in a sorted list of integers

If you were to take random positive integers, put them into a list, and sort them is there anyway to find the expected value of the kth item in the list? The list is sorted in ascending order. By ...
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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 ...
94 views

### 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 ...
716 views

### 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 ...
832 views

### 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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### 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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### 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 ...
309 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 ...
137 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 ...
222 views

### 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 ...
680 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 ...
2k views

### 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 ...
1k views

### Benefits of using genetic algorithm

Can anyone explain to me the benefits of the genetic algorithm compared to other traditional search and optimization methods?
1k views

### 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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### 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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### 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 ...
214 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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### 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 ...
308 views

### 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 ...
945 views

### 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 ...
233 views

### 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 ...
240 views

### 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 ...
579 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 ...
948 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 ...
281 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 ...