aps2020
Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics (by majianthu)
vip
Variable Importance Plots (VIPs) (by koalaverse)
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aps2020 | vip | |
---|---|---|
2 | 1 | |
17 | 186 | |
- | 1.1% | |
0.0 | 6.5 | |
almost 2 years ago | 6 months ago | |
R | R | |
GNU General Public License v3.0 only | - |
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.
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.
aps2020
Posts with mentions or reviews of aps2020.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[R] Feature selection algorithms for psychometric questions when the predicted variable is multi-dimensional?
try Copula Entropy for feature/variable selection. see my paper "Variable Selection with Copula Entropy". The code for the paper is at here, in which the R package 'copent' is used.
- [Q] Feature selection (>600 features)
vip
Posts with mentions or reviews of vip.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing aps2020 and vip you can also consider the following projects:
evalml - EvalML is an AutoML library written in python.
miceRanger - miceRanger: Fast Imputation with Random Forests in R
dcor - Distance correlation and related E-statistics in Python
ParBayesianOptimization - Parallelizable Bayesian Optimization in R
tmle3mopttx - 🎯 💯 Targeted Learning and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention
lmtp - :package: Non-parametric Causal Effects Based on Modified Treatment Policies :crystal_ball:
mlr3learners - Recommended learners for mlr3
textfeatures - 👷♂️ A simple package for extracting useful features from character objects 👷♀️