ParBayesianOptimization VS miceRanger

Compare ParBayesianOptimization vs miceRanger and see what are their differences.

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ParBayesianOptimization miceRanger
1 1
99 61
- -
0.0 0.0
over 1 year ago over 1 year ago
R R
- GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ParBayesianOptimization

Posts with mentions or reviews of ParBayesianOptimization. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning ParBayesianOptimization yet.
Tracking mentions began in Dec 2020.

miceRanger

Posts with mentions or reviews of miceRanger. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-14.
  • Multiple imputation packages in R
    2 projects | /r/Rlanguage | 14 Sep 2021
    I developed miceRanger because the mice package uses a really slow implementation of random forests. It has a bunch of plotting capabilities and can impute new datasets without re-training the models used in the mice procedure.

What are some alternatives?

When comparing ParBayesianOptimization and miceRanger you can also consider the following projects:

mice - Multivariate Imputation by Chained Equations

vip - Variable Importance Plots (VIPs)

mlr3learners - Recommended learners for mlr3

tmle3mopttx - 🎯 💯 Targeted Learning and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention

mlr3 - mlr3: Machine Learning in R - next generation

ggplot2 - An implementation of the Grammar of Graphics in R

tweetbotornot - 🤖 R package for detecting Twitter bots via machine learning

causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning