close

Showing 3 of total 3 results (show query)

sizespectrum

mizer:Dynamic Multi-Species Size Spectrum Modelling

A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.

Maintained by Gustav Delius. Last updated 2 months ago.

ecosystem-modelfish-population-dynamicsfisheriesfisheries-managementmarine-ecosystempopulation-dynamicssimulationsize-structurespecies-interactionstransport-equationcpp

39 stars 9.41 score 207 scripts

adriancorrendo

metrica:Prediction Performance Metrics

A compilation of more than 80 functions designed to quantitatively and visually evaluate prediction performance of regression (continuous variables) and classification (categorical variables) of point-forecast models (e.g. APSIM, DSSAT, DNDC, supervised Machine Learning). For regression, it includes functions to generate plots (scatter, tiles, density, & Bland-Altman plot), and to estimate error metrics (e.g. MBE, MAE, RMSE), error decomposition (e.g. lack of accuracy-precision), model efficiency (e.g. NSE, E1, KGE), indices of agreement (e.g. d, RAC), goodness of fit (e.g. r, R2), adjusted correlation coefficients (e.g. CCC, dcorr), symmetric regression coefficients (intercept, slope), and mean absolute scaled error (MASE) for time series predictions. For classification (binomial and multinomial), it offers functions to generate and plot confusion matrices, and to estimate performance metrics such as accuracy, precision, recall, specificity, F-score, Cohen's Kappa, G-mean, and many more. For more details visit the vignettes <https://adriancorrendo.github.io/metrica/>.

Maintained by Adrian A. Correndo. Last updated 9 months ago.

77 stars 7.88 score 49 scripts

serkor1

SLmetrics:Machine Learning Performance Evaluation on Steroids

Performance evaluation metrics for supervised and unsupervised machine learning, statistical learning and artificial intelligence applications. Core computations are implemented in 'C++' for scalability and efficiency.

Maintained by Serkan Korkmaz. Last updated 2 days ago.

cppdata-analysisdata-scienceeigen3machine-learningperformance-metricsrcpprcppeigenstatisticssupervised-learningcppopenmp

22 stars 6.56 score

: