vswift VS textfeatures

Compare vswift vs textfeatures and see what are their differences.

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vswift textfeatures
1 1
1 167
- -
8.9 0.0
about 1 month ago over 3 years ago
R R
MIT License 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.

vswift

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

textfeatures

Posts with mentions or reviews of textfeatures. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-18.

What are some alternatives?

When comparing vswift and textfeatures you can also consider the following projects:

mlr3learners - Recommended learners for mlr3

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

Empirical_Study_of_Ensemble_Learning_Methods - Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning

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

mlr3 - mlr3: Machine Learning in R - next generation

r-naive-bayes-showcase - Naive Bayes classifier in R

tweetbotornot2 - 🔍🐦🤖 Detect Twitter Bots!

vip - Variable Importance Plots (VIPs)

machine_learning_basics - Plain python implementations of basic machine learning algorithms

spacyr - R wrapper to spaCy NLP

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

awesome-computational-social-science - A list of awesome resources for Computational Social Science