Showing 10 of total 10 results (show query)
dselivanov
text2vec:Modern Text Mining Framework for R
Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. This package provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.
Maintained by Dmitriy Selivanov. Last updated 8 months ago.
glovelatent-dirichlet-allocationnatural-language-processingtext-miningtopic-modelingvectorizationword-embeddingsword2veccpp
860 stars 13.48 score 1.3k scripts 23 dependents
momx
Momocs:Morphometrics using R
The goal of 'Momocs' is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.
Maintained by Vincent Bonhomme. Last updated 1 years ago.
51 stars 7.42 score 346 scripts
cran
topicmodels:Topic Models
Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.
Maintained by Bettina Grün. Last updated 8 months ago.
8 stars 6.37 score 16 dependents
odelmarcelle
sentopics:Tools for Joint Sentiment and Topic Analysis of Textual Data
A framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.
Maintained by Olivier Delmarcelle. Last updated 3 months ago.
8 stars 5.38 score 5 scripts
jonasrieger
ldaPrototype:Prototype of Multiple Latent Dirichlet Allocation Runs
Determine a Prototype from a number of runs of Latent Dirichlet Allocation (LDA) measuring its similarities with S-CLOP: A procedure to select the LDA run with highest mean pairwise similarity, which is measured by S-CLOP (Similarity of multiple sets by Clustering with Local Pruning), to all other runs. LDA runs are specified by its assignments leading to estimators for distribution parameters. Repeated runs lead to different results, which we encounter by choosing the most representative LDA run as prototype.
Maintained by Jonas Rieger. Last updated 2 years ago.
latent-dirichlet-allocationldamodel-selectionmodelselectionreliabilitytext-miningtextdatatopic-modeltopic-modelstopic-similaritiestopicmodelingtopicmodelling
8 stars 4.44 score 23 scripts 1 dependents
dyfanjones
sagemaker:R SDK for `AWS Sagemaker`
A library for training and deploying machine learning models on Amazon SageMaker <https://aws.amazon.com/sagemaker/> using R through `paws SDK`.
Maintained by Dyfan Jones. Last updated 3 years ago.
amazon-sagemakerawsmachine-learningsagemakersdk
12 stars 2.78 score 6 scriptsdyfanjones
sagemaker.mlframework:sagemaker machine learning developed by amazon
`sagemaker` machine learning developed by amazon.
Maintained by Dyfan Jones. Last updated 3 years ago.
amazon-sagemakerawsmachine-learningsagemakersdk
2.48 score 2 dependents
aflapan
biClassify:Binary Classification Using Extensions of Discriminant Analysis
Implements methods for sample size reduction within Linear and Quadratic Discriminant Analysis in Lapanowski and Gaynanova (2020) <arXiv:2005.03858>. Also includes methods for non-linear discriminant analysis with simultaneous sparse feature selection in Lapanowski and Gaynanova (2019) PMLR 89:1704-1713.
Maintained by Alexander F. Lapanowski. Last updated 3 years ago.
2.00 score 4 scriptscran
LDAandLDAS:Linkage Disequilibrium of Ancestry (LDA) and LDA Score (LDAS)
Computation of linkage disequilibrium of ancestry (LDA) and linkage disequilibrium of ancestry score (LDAS). LDA calculates the pairwise linkage disequilibrium of ancestry between single nucleotide polymorphisms (SNPs). LDAS calculates the LDA score of SNPs. The methods are described in Barrie W, Yang Y, Irving-Pease E.K, et al (2024) <doi:10.1038/s41586-023-06618-z>.
Maintained by Yaoling Yang. Last updated 1 years ago.
1.70 score
blansche
fdm2id:Data Mining and R Programming for Beginners
Contains functions to simplify the use of data mining methods (classification, regression, clustering, etc.), for students and beginners in R programming. Various R packages are used and wrappers are built around the main functions, to standardize the use of data mining methods (input/output): it brings a certain loss of flexibility, but also a gain of simplicity. The package name came from the French "Fouille de Données en Master 2 Informatique Décisionnelle".
Maintained by Alexandre Blansché. Last updated 2 years ago.
1 stars 1.62 score 42 scripts