Questions tagged [genetic-algorithms]

A class of optimization algorithms inspired by (or emulating) biological evolution.

50 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
3
votes
0answers
287 views

Evolutionary algorithms for model selection

I've recently come across a few encounters where people are using genetic programming or genetic algorithms to build "best" performing models. gplearn is an example of genetic programming used for ...
3
votes
0answers
223 views

My difficulties with regard to estimation of parameters using genetic algorithms in R language

* I just came to know that the post was unlocked, meanwhile I have re-posted the question on this forum. But I am posting the edited version here as well as I am unaware of the rules in this regard. * ...
3
votes
0answers
214 views

Should I use random fixed mutation or random percentual mutation?

I'm evolving neural networks, partly by mutating connection weights and neuron biases. Right now i'm mutating weights as follows: ...
3
votes
0answers
66 views

Efficiency of crossover in genetic algorithms

This question is basically clone of . I am reposting it here because in my opinion it is more appropriate site and because I didn't actually see answer itself. Quote from there: I understand the ...
3
votes
0answers
797 views

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 ...
3
votes
0answers
550 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 ...
2
votes
0answers
25 views

Best Statistical Techniques for Order Sensitive Data

Problem I am writing a Genetic Algorithm (GA) that aims to find the best order of performing a given set of tasks to fulfill an objective. Imagine there are a set of tasks ...
2
votes
2answers
237 views

Is the NEAT algorithm unbalanced?

So I'm developing an implementation of the NEAT algorithm. I understand how it works. But during my testing phase I saw something interesting, related to this quote: In the add node mutation an ...
2
votes
0answers
87 views

Difference or similarity between a biology and genetic algorithm

What id the difference/similarity between a biological chromosome and a chromosome from a genetic algorithm? A biological chromosome represents a specific living organism who can be a result of an ...
2
votes
0answers
111 views

Cheaper/faster method to estimate uncertainties than bootstrap

I'm using a genetic algorithm (GA) to estimate the minimum value of a likelihood function $L[x]$ which is too complicated to evaluate mathematically. This likelihood function quantifies the goodness ...
1
vote
0answers
19 views

Human interpretable Neural Networks?

Say I made Neural Network Trading Algorithm. How to understand what it does? Example How human would do the job. Human look at charts and thinks, and then develops an algorithm like "make ...
1
vote
0answers
19 views

How to minimise a quantity using a Genetic Algorithm

I'm somewhat new to Genetic Algorithms and I've been exploring the use of them to minimize a quantity (Y), where my optimum value is a small negative value. I've implemented an algorithm that has a ...
1
vote
0answers
36 views

Why don't get the expected result despite the high accuracy rate?

I have a database of images of 213 examples (7 classes). First, I extracted the features where I got 212 features. CAD, I maintain a data matrix of 213x212. I used the genetic algorithm for both ...
1
vote
0answers
23 views

Statistical test suggestion for algorithm comparison

I have 8 different algorithms (based on well-known genetic algorithm). Each algorithm is tested with 50 independent runs for 4 different benchmark problems. Also, each problem has 24 different cases ...
1
vote
0answers
16 views

Particle Swarm Optimisation Explained

Is anyone able to provide an intuitive explanation of how particle swarm optimisation works? For example how to minimise a function f(x,y,z). Also, does particle swarm optimisation work for multi-...
1
vote
0answers
22 views

Ideas for determining the optimal sequence of calls and emails to maximize the probability of a sales lead converting to a sale?

I have a large data set of sales leads that are in the form of a lead_id, a sequence of binary integers that denote the order of emails and phone calls made to a sales lead, and the binary outcome of ...
1
vote
0answers
73 views

Best method to investigate treatment effect after creating a Matched control group using Gentic Matching (with replacement)?

Project background: I have data on patients who received varying amounts of therapy dose during treatment of stroke-induced paralysis. I wish to investigate if there are differences in motor-function ...
1
vote
0answers
25 views

ML for optimizing manufacturing tool programming

I work with some folks who program a rather complex tool that uses a pair of motion systems and a controllable light source to do some material processing. In general it does a pretty good job by ...
1
vote
0answers
32 views

How can I select which genetic operators configuration for a permutation problem and why?

I am try to solve a combinatory problem using genetic algorithms and the GA package in R. Essentially my problem statement is the following: Given a fitness function $f(X)$, where $X$ is a division ...
1
vote
0answers
70 views

How to modify a Genetic Algorithm to optimise dependent variables?

Say that I want to build a classifier that performs the following: Encode each feature from a dataset (X encodings available) Perform a number of computations on the encoded values (Y number of ...
1
vote
0answers
32 views

Feedforward NN for GA with multiple types of actions (outputs)

I'm working on an AI model that needs to efficiently assign jobs to workers depending on job.requiredResources and worker.totalResources`. When I say efficiently, I ...
1
vote
0answers
497 views

Genetic algorithms on Titanic data set - overfitting or the real deal?

As you're likely aware, predicting survivors from the Titanic disaster has been turned into an educational data science challenge on Kaggle.com. A few "competitors" have perfect scores, presumably due ...
1
vote
0answers
460 views

Limiting selected variables in Genetic Algorithm Feature Selection

I am trying to find a set of good predictors using carets GA in R to train a few classification models. My dataset consists of around 4500 rows of 96 independent variables. I want to use GA to, ...
1
vote
0answers
40 views

Genetic programming for a function of functions of inputs

Given a vector of variables $X=(x_1, x_2, ..., x_n)$ I have previously used genetic programming for deriving an expression for a function $y=f(X)$ from a training dataset of tuples $<X, y>$. ...
1
vote
0answers
1k views

How can we use genetic algorithm for curve fitting?

I want to use genetic algorithm in order to fit a curve to some data, or in other words, to estimate some equation that describes the relationship. Suppose that I select the equation to be a ...
1
vote
0answers
87 views

Which ML algorithm is suitable for the following problem?

Assume i have x states each defined by an n-dimensional feature vector. In addition i have a set of actions which can be taken in each state resulting in a state action score. What would be an ...
1
vote
0answers
219 views

Optimize number of layers and neurons with an optimization algorithm

I have a neural network that i want optimize number of hidden layers and neurons in every layer using an optimization algorithm like ...
1
vote
0answers
97 views

pairing algorithm in R

I have two sets of elements M and N, and a scalar-valued distance/similarity function between one element from M and one from N. The problem is to generate a set of pairs (one item from M and one ...
1
vote
0answers
246 views

Prioritization based on three factors

Background: Sales reps visit doctor and detail about a product/drug. One visit is termed as one call. In return he writes the prescriptions to doctors prescribing that particular drug. Problem ...
1
vote
1answer
203 views

Find initial central points of k-means clustering using genetic algorithm

I am implementing genetic algorithm in order to find best initial central points for k-means clustering algorithm. I use this formula for fitness function: $$\sum_{\chi_{j}\in X}{\min_{1\le i\le k}(\...
1
vote
1answer
3k 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 ...
0
votes
0answers
13 views

Single optimum parameter output for multi-objective optimization (genetic algorithms)

If this question is out of scope for this forum, before closing it please advise me on a better platform to ask my question! I'm very new to this field so apologies if my questions are not clear. I am ...
0
votes
0answers
18 views

Genetic algorithm (GA) for training a generalized linear discriminate classifier

How can genetic algorithms (GA) be used for training a generalized linear discriminate classifier? What would the genes/chromosomes and fitness function be? How can genetic programming (GP) be used ...
0
votes
0answers
15 views

Create Fitness score/highscore with multiple variables

I am currently building a Neural network( + genetic algorithms) that learns to fly a 2D drone to a target. My goal is that it achieve all tasks as fast a possible but I want the drone to also fly ...
0
votes
0answers
15 views

Question on Machine Learning to Generate Genetic Algorithms with Highest Sensitivity and Specificity Values

I am new to this website, but I am a researcher who has no experience in ML who is trying to generate molecular algorithms that use a combination of genetic markers in order to correctly predict ...
0
votes
1answer
58 views

Sampling from distribution parametrized by $ \log(1-p) $ given $ \log (p) $

The context for the problem is that I'm working with a modified genetic algorithm where the fitness score of each chromosome is given by a log-probability $ \log(p) \in (-\infty, 0) $. Thus, I have a ...
0
votes
1answer
22 views

What are the rules for evolving a partially connected neural network using a genetic algorithm?

I am working on a project where I need to implement the NEAT algorithm in python. after doing some research I came across an issue that I can't seem to find a solution for online, I hope this is the ...
0
votes
0answers
10 views

Can the same individual from a population be chosen in a genetic algorithm?

One population contains 10 individuals, from these 10, 8 are picked based on a selection mechanism. Let's say they are picked using the rank based selection mechanism (so the best ranked has a higher ...
0
votes
0answers
70 views

Can genetic algorithms be used for statistical inference?

Is it possible to use genetic algorithms for (pseudo-) statistical inference? I.e., something like constructing confidence intervals from stable generations? I hope my question make sense & ...
0
votes
0answers
136 views

Cross - entropy for two variables with different prob. distributions

Let us say that we have given two random variables with different prob. distributions: A = [0.1, 0, 0.5, ...] B = [0.3, 0.1, 0.03, ...] What should I do when I want to compute the reformulated cross-...
0
votes
1answer
136 views

Assignment Problem (Linear Programming, Genetic Algorithm, etc.)

I'm looking for advice on how I should approach a specific problem. Some background first: The problem is about shipments falling into a bin. There are 19 such bins, which are further sorted into 20 ...
0
votes
0answers
58 views

Training ANN sharing parameters, which algorithm to favor?

Hi all I have a question concerning the algorithm I should use to perform the training of multiple feedforward neural networks with shared parameters. The problem I am trying to solve is a boundary ...
0
votes
0answers
31 views

Optimization of a noisy function with binary output

What frameworks exist to optimize the following problem: $\theta^\ast = \operatorname*{argmin}\limits_{\theta \in \Theta} f(\theta)$ with the characteristic that $f$ is noisy and has a binary output ...
0
votes
1answer
40 views

Would a genetic algorithm be used for this type of scheduling optimization?

Let me preface this by saying I'm not an experienced data scientist/statistician so I apologize if this is trivial. My problem statement is as follows: There are N events that happen from time A to ...
0
votes
0answers
126 views

Sample a probability distribution with an evolutionary algorithm?

I've been doing some initial level reading on Markov chain Monte Carlo (MCMC). For what I can tell given a probability distribution $P(x_1, x_2, ..., x_N)$ (dependent on $N$ parameters), MCMC ...
0
votes
0answers
102 views

Approach to optimize parameters to maximize throughput via Genetic Algorithm

I need some ideas to approach the following problem. Problem: I need to set optimum parameters to achieve maximum output dependent on the input type. Input: I have 5 different rocks (say, various ...
0
votes
0answers
20 views

Optimizing individuals by direct comparison (fitness is dependent on other individuals)

I'm participating in an AI challenge and would like to use machine learning or genetic algorithms to optimize my strategy. The strategy is represented by a list of floats (size=7) which are weights ...
0
votes
0answers
38 views

Computer measurements: Within or between subjects?

First of al, thank you for your time. Question My independent variable is the amount of computations that are performed. My dependent variable is the fit of the model (fitness) My control variables ...
0
votes
0answers
1k views

Minimum Number of Variables for Effective use of the Genetic Algorithm

From my understanding of the genetic algorithm the population consists of individuals, where each individual is a potential solution made up of "genes", and each gene is a variable. So for a cost ...
0
votes
0answers
614 views

Population size for Genetic algorithm - rule of thumb

I have a 4-dimensional function $F(a,b,c,d)$ which I need to optimize (find the minimum) Each of the 4 parameters of my function $(a,b,c,d)$ are made to vary in steps over a range, so each one can ...