R-universe search: "evaluation-metrics"

Showing 3 of total 3 results (show query)

schuch666

eva3dm:Evaluation of 3D Meteorological and Air Quality Models

Provides tools for post-process, evaluate and visualize results from 3d Meteorological and Air Quality models against point observations (i.e. surface stations) and grid (i.e. satellite) observations.

Maintained by Daniel Schuch. Last updated 24 days ago.

air-quality-model air-quality-model-evaluation atmos atmosphere atmospheric-chemistry atmospheric-modelling atmospheric-models atmospheric-science evaluation model-evaluation model-evaluation-metrics wrf-chem

51.7 match 4 stars 4.75 score 3 scripts

cleanzr

clevr:Clustering and Link Prediction Evaluation in R

Tools for evaluating link prediction and clustering algorithms with respect to ground truth. Includes efficient implementations of common performance measures such as pairwise precision/recall, cluster homogeneity/completeness, variation of information, Rand index etc.

Maintained by Neil Marchant. Last updated 2 years ago.

clustering-evaluation entity-resolution evaluation-metrics link-prediction record-linkage cpp

29.9 match 12 stars 4.77 score 49 scripts

nunompmoniz

IRon:Solving Imbalanced Regression Tasks

Imbalanced domain learning has almost exclusively focused on solving classification tasks, where the objective is to predict cases labelled with a rare class accurately. Such a well-defined approach for regression tasks lacked due to two main factors. First, standard regression tasks assume that each value is equally important to the user. Second, standard evaluation metrics focus on assessing the performance of the model on the most common cases. This package contains methods to tackle imbalanced domain learning problems in regression tasks, where the objective is to predict extreme (rare) values. The methods contained in this package are: 1) an automatic and non-parametric method to obtain such relevance functions; 2) visualisation tools; 3) suite of evaluation measures for optimisation/validation processes; 4) the squared-error relevance area measure, an evaluation metric tailored for imbalanced regression tasks. More information can be found in Ribeiro and Moniz (2020) <doi:10.1007/s10994-020-05900-9>.

Maintained by Nuno Moniz. Last updated 2 years ago.

evaluation-metrics imbalance-data imbalanced-learning machine-learning regression

22.3 match 19 stars 3.86 score 38 scripts