I would like kindly to ask if anybody has an idea how to build a genetic algorithm GA model that is able to solve the "diet problem" with constraints and minimization objective in R?
thank you and appreciate your contribution
I use rgenoud package in R. See paper here: http://sekhon.berkeley.edu/papers/rgenoudJSS.pdf
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I used Caret to create a regression model of a dataset in R, and I wish to find this equation for usage in other websites (e.g. Desmos). I am unable to find info anywhere on how to do this, so if anyone has answers, that would be much appreciated! :D
Hello stackoverflow community,
Im working on a uni-project in which we try to create Bayesian Network Classifier from data in R.
Ideally the classifier should be based on a General Bayesian Network (GNB) or a BN Augmented Naive Bayes(BAN).
Unfortunately Im yet to find a suitabel package to create either of those nets in R.
My research led me to the following two packages:
bnclassify, the most prominent package for BN classification, doesnt include GNBs or BANs at all.
bnlearn offers the possibility to learn GNBs but according to the creator the learning is focused on returning the correct dependence structure rather than maximizing the predictive accuracy for classification. I've tried to use them for my classification problem nonetheless but the result was underwhelming.
So my question is if anyone knows a R package to classify with GNBs or BANs
OR how to work with the GNBs fron bnlearn to improve their predictive accuracy for classification problems.
Thanks you for your help in advance.
Best Regards
I am working with a set of 42345 patients, from those, I establish subsets as Obese/non-Obese etc
I am wondering if there is a way in R to estimate the regression to the mean.
This may be a good resource in case someone who knows base R can help me. From this paper, I would be interested in expressing this equation in R:
Thank you very much in advance.
Best regards
I'm wondering if ther is a package to plot the feasible region (based on the constraints) and the optimal solution for linear programming in Julia Language using Juno. Do you know a way to do this? Suppose we have a LP problem and want to visualize the region and optimal solution. Is there a package to do this? How can I do this. I would appreciate so much your help. Thanks.
I'm searching for a package or a way to use the algorithm Adaboost.R2 (adaboost for regression) in R. I can use it in ROOT and change my loss function in "quadratic" and I want to get the same thing in R. Someone can help me? Thanks.