Machine Learning in R
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Updated
May 6, 2024 - R
Machine Learning in R
Collection of various algorithms implemented in R.
Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.
R Package for Time Series Clustering Along with Optimizations for DTW
Misc Statistics and Machine Learning codes in R
REVOLVER - Repeated Evolution in Cancer
Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).
simpler single cell RNAseq data clustering
Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
The Machine Learning Module
Structured Graph Learning via Laplacian Spectral Constraints (NeurIPS 2019)
Visualise Clusterings at Different Resolutions
Process and Analyze Mouse-Tracking Data
R scripts to reproduce analyses in our paper comparing clustering methods for high-dimensional cytometry data
Monte Carlo Reference-based Consensus Clustering
Compute Convex (Bi)Clustering Solutions via Algorithmic Regularization
Assessing the purity of single cell population
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