M3C - Monte Carlo Reference-based Consensus Clustering
M3C is a consensus clustering algorithm that uses a Monte Carlo simulation to eliminate overestimation of K and can reject the null hypothesis K=1.
Last updated 5 months ago
clusteringgeneexpressiontranscriptionrnaseqsequencingimmunooncology
6.59 score 1 dependents 174 scripts 1.1k downloadsSpectrum - Fast Adaptive Spectral Clustering for Single and Multi-View Data
A self-tuning spectral clustering method for single or multi-view data. 'Spectrum' uses a new type of adaptive density aware kernel that strengthens connections in the graph based on common nearest neighbours. It uses a tensor product graph data integration and diffusion procedure to integrate different data sources and reduce noise. 'Spectrum' uses either the eigengap or multimodality gap heuristics to determine the number of clusters. The method is sufficiently flexible so that a wide range of Gaussian and non-Gaussian structures can be clustered with automatic selection of K.
Last updated 5 years ago
clusteringspectral-clustering
5.99 score 7 stars 1 dependents 47 scripts 485 downloadsMLeval - Machine Learning Model Evaluation
Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and PR gain curves. 'MLeval' accepts a data frame of class probabilities and ground truth labels, or, it can automatically interpret the Caret train function results from repeated cross validation, then select the best model and analyse the results. 'MLeval' produces a range of evaluation metrics with confidence intervals.
Last updated 5 years ago
5.71 score 6 stars 144 scripts 679 downloads