R_THEME
Multiblock exploratory modeler
A software framework for exploring and predicting relationships in multiblock datasets using a combination of statistical modeling and machine learning techniques.
THEmatic Model Exploration is a both exploratory and predictive multiblock-multiequation-technique.
1 stars
0 watching
1 forks
Language: R
last commit: about 1 year ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
modeloriented/modelstudio | A tool for creating interactive, model-agnostic explanations of machine learning models in R | 326 |
marcelrobeer/explabox | An exploratory tool for analyzing and understanding machine learning models | 15 |
rmarko/explainprediction | An R package for explaining the predictions made by machine learning models in data science applications. | 2 |
modeloriented/ibreakdown | A tool for explaining predictions from machine learning models by attributing them to specific input variables and their interactions. | 81 |
boxuancui/dataexplorer | Automates data exploration and treatment tasks in R | 512 |
mi2datalab/pybreakdown | A Python implementation of a method to explain the predictions of machine learning models | 41 |
theme-ontology/theming | Develops a literary thematic knowledgebase to support computational analyses in fiction studies | 20 |
model-r/modler | An ecological niche modeling workflow tool | 51 |
pennisetum/jaca | An R package that provides a statistical framework for analyzing multi-view data | 3 |
mrke/nichemapr | An R implementation of biophysical modelling tools for species survival and ecology | 63 |
rrrlw/icon | Provides access to complex systems datasets from the Index of Complex Networks (ICON) database. | 7 |
philipmostert/pointedsdms | Tools for building and evaluating integrated species distribution models from disparate datasets | 24 |
pbs-assess/sdmtmb | An R package for fitting spatial and spatiotemporal GLMMs using TMB | 187 |
modeloriented/drwhy | A collection of tools and guidelines for building responsible machine learning models | 680 |
nrel/resstock | Develops detailed models of residential building characteristics and simulates energy performance | 108 |