Search Results for "algorithms"

Glycometrics is a collection of algorithms that provide metrics for glycaemic variability. Its application is mainly in theoretical endocrinology and diabetes research.

DiagrammeR is an R package to create, manipulate, and visualize network graphs, flowcharts, diagrams, and more using Graphviz and Mermaid syntax. Integrates with RMarkdown and Shiny apps, supports node/edge traversal, and graph analysis algorithms, making it ideal for documenting processes, causal relationships, or data pipelines.

...So we developed a user-friendly and powerful software/webserver, MetEx, to both enable implementation of classical peak detection-based annotation and a new annotation method based on targeted extraction algorithms. The new annotation method based on targeted extraction algorithms can annotate more than 2 times metabolites than classical peak detection-based annotation method because it reduces the loss of metabolite signal in the data preprocessing process.

...It is written in a way that you can extend it yourself or deviate from the implemented convenience methods and construct your own complex experiments or algorithms.

...It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories.

RStan is the R interface to Stan, a C++ library for statistical modeling and high-performance statistical computation. It lets users specify models in the Stan modeling language (for Bayesian inference), compile them, and perform inference from R. Key inference approaches include full Bayesian inference via Hamiltonian Monte Carlo (specifically the No-U-Turn Sampler, NUTS), approximate Bayesian inference via variational methods, and optimization (penalized likelihood). RStan integrates with...