Showing 6 of total 6 results (show query)
bioc
msImpute:Imputation of label-free mass spectrometry peptides
MsImpute is a package for imputation of peptide intensity in proteomics experiments. It additionally contains tools for MAR/MNAR diagnosis and assessment of distortions to the probability distribution of the data post imputation. The missing values are imputed by low-rank approximation of the underlying data matrix if they are MAR (method = "v2"), by Barycenter approach if missingness is MNAR ("v2-mnar"), or by Peptide Identity Propagation (PIP).
Maintained by Soroor Hediyeh-zadeh. Last updated 5 months ago.
massspectrometryproteomicssoftwareimputation-algorithmlabel-free-proteomicslow-rank-approximation
14 stars 5.15 score 7 scripts
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
cran
SKNN:A Super K-Nearest Neighbor (SKNN) Classification Algorithm
It's a Super K-Nearest Neighbor classification method with using kernel density to describe weight of the distance between a training observation and the testing sample.
Maintained by Yarong Yang. Last updated 6 months ago.
1.78 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
guangbaog
DTSR:Distributed Trimmed Scores Regression for Handling Missing Data
Provides functions for handling missing data using Distributed Trimmed Scores Regression and other imputation methods. It includes facilities for data imputation, evaluation metrics, and clustering analysis. It is designed to work in distributed computing environments to handle large datasets efficiently. The philosophy of the package is described in Guo G. (2024) <doi:10.1080/03610918.2022.2091779>.
Maintained by Guangbao Guo. Last updated 5 months ago.
1.00 score