Showing 12 of total 12 results (show query)
mhahsler
recommenderlab:Lab for Developing and Testing Recommender Algorithms
Provides a research infrastructure to develop and evaluate collaborative filtering recommender algorithms. This includes a sparse representation for user-item matrices, many popular algorithms, top-N recommendations, and cross-validation. Hahsler (2022) <doi:10.48550/arXiv.2205.12371>.
Maintained by Michael Hahsler. Last updated 4 days ago.
collaborative-filteringrecommender-system
214 stars 10.42 score 840 scripts 2 dependents
sachaepskamp
bootnet:Bootstrap Methods for Various Network Estimation Routines
Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices <doi:10.3758/s13428-017-0862-1>. Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for various estimation routines.
Maintained by Sacha Epskamp. Last updated 5 months ago.
32 stars 8.94 score 155 scripts 3 dependents
michbur
biogram:N-Gram Analysis of Biological Sequences
Tools for extraction and analysis of various n-grams (k-mers) derived from biological sequences (proteins or nucleic acids). Contains QuiPT (quick permutation test) for fast feature-filtering of the n-gram data.
Maintained by Michal Burdukiewicz. Last updated 7 months ago.
biological-sequencesngram-analysis
10 stars 7.50 score 87 scripts 3 dependents
bnprks
BPCells:Single Cell Counts Matrices to PCA
> Efficient operations for single cell ATAC-seq fragments and RNA counts matrices. Interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.
Maintained by Benjamin Parks. Last updated 2 months ago.
184 stars 7.48 score 172 scripts
jonclayden
mmand:Mathematical Morphology in Any Number of Dimensions
Provides tools for performing mathematical morphology operations, such as erosion and dilation, on data of arbitrary dimensionality. Can also be used for finding connected components, resampling, filtering, smoothing and other image processing-style operations.
Maintained by Jon Clayden. Last updated 1 years ago.
image-processingmorphologyresamplingcppopenmp
37 stars 7.42 score 223 scripts 9 dependents
business-science
correlationfunnel:Speed Up Exploratory Data Analysis (EDA) with the Correlation Funnel
Speeds up exploratory data analysis (EDA) by providing a succinct workflow and interactive visualization tools for understanding which features have relationships to target (response). Uses binary correlation analysis to determine relationship. Default correlation method is the Pearson method. Lian Duan, W Nick Street, Yanchi Liu, Songhua Xu, and Brook Wu (2014) <doi:10.1145/2637484>.
Maintained by Matt Dancho. Last updated 1 years ago.
correlationexploratory-analysisexploratory-data-analysisexploratory-data-visualizationstidyverse
137 stars 7.20 score 115 scripts
alexchristensen
NetworkToolbox:Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis
Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. Methods include various filtering methods and approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershgoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>). Brain methods include the recently developed Connectome Predictive Modeling (see references in package). Also implements several network measures including local network characteristics (e.g., centrality), community-level network characteristics (e.g., community centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.
Maintained by Alexander Christensen. Last updated 2 years ago.
23 stars 7.04 score 101 scripts 4 dependents
cran
biclust:BiCluster Algorithms
The main function biclust() provides several algorithms to find biclusters in two-dimensional data: Cheng and Church (2000, ISBN:1-57735-115-0), spectral (2003) <doi:10.1101/gr.648603>, plaid model (2005) <doi:10.1016/j.csda.2004.02.003>, xmotifs (2003) <doi:10.1142/9789812776303_0008> and bimax (2006) <doi:10.1093/bioinformatics/btl060>. In addition, the package provides methods for data preprocessing (normalization and discretisation), visualisation, and validation of bicluster solutions.
Maintained by Sebastian Kaiser. Last updated 2 years ago.
3 stars 4.74 score 16 dependentsjonclayden
imbibe:A Pipe-Friendly Image Calculator
Provides a set of fast, chainable image-processing operations which are applicable to images of two, three or four dimensions, particularly medical images.
Maintained by Jon Clayden. Last updated 4 years ago.
14 stars 4.32 score 3 scripts
yunuuuu
BPCellsArray:Using BPCells as a DelayedArray Backend
Implements a DelayedArray backend for reading and writing arrays in the BPCells storage layout. The resulting BPCells*Arrays are compatible with all Bioconductor pipelines that can accept DelayedArray instances.
Maintained by Yun Peng. Last updated 8 months ago.
softwaredataimportdatarepresentationinfrastructuresingle-cell
7 stars 4.32 score
profyliu
bsnsing:Bsnsing: A Decision Tree Induction Method Based on Recursive Optimal Boolean Rule Composition
The bsnsing package provides functions for training a decision tree classifier, making predictions and generating latex code for plotting. It solves the two-class and multi-class classification problems under the supervised learning paradigm. While building a decision tree, bsnsing uses a Boolean rule involving multiple variables to split a node. Each split rule is identified by solving an optimization problem. Use the bsnsing function to build a tree, the predict function to make predictions and the show function to plot the tree. The paper is at <arXiv:2205.15263>. Source code and more data sets are at <https://github.com/profyliu/bsnsing>.
Maintained by Yanchao Liu. Last updated 3 years ago.
7 stars 3.54 score 1 scripts