Introduction | Example Data | Model Fittig and Prediction | Revised Stacking Algorithm for Continuous Outcome | Revised Stacking Algorithm for Binary Outcome | Revised Stacking Algorithm for Mix Outcome | Specifying Models in Step 1 and Step 2 | Specify Different Base Learners for Different Outcomes within One Step | User-Defined Base Learners | Modify Arguments for Existing Base Learners | Define New Base Learners | Performance Comparison | Reference
Package: MTPS 1.0.2
Li Xing
MTPS: Multi-Task Prediction using Stacking Algorithms
Simultaneous multiple outcomes prediction based on revised stacking algorithms, which enables the integration of information from predictions of individual models. An implementation of methodologies proposed in our paper: Li Xing, Mary L Lesperance, Xuekui Zhang. (2019) Bioinformatics, "Simultaneous prediction of multiple outcomes using revised stacking algorithms" <doi:10.1093/bioinformatics/btz531>.
Authors:
MTPS_1.0.2.tar.gz
MTPS_1.0.2.zip(r-4.7-any)MTPS_1.0.2.zip(r-4.6-any)MTPS_1.0.2.zip(r-4.5-any)
MTPS_1.0.2.tgz(r-4.6-any)MTPS_1.0.2.tgz(r-4.5-any)
MTPS_1.0.2.tar.gz(r-4.7-any)MTPS_1.0.2.tar.gz(r-4.6-any)
MTPS_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MTPS/json (API)
| # Install 'MTPS' in R: |
| install.packages('MTPS', repos = c('https://ubclxing.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- ctn.plot.data - Internal Data Object
- mix.plot.data - Internal Data Object
- mse.data - Internal Data Object
- pred.mix.rs - Internal Data Object
- pred.prs.std - Internal Data Object
- XX - HIV Drug Resistance Database
- y.test.bin - Internal Data Object
- y.test.mix - Internal Data Object
- YY - HIV Drug Resistance Database
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:8860ad0aed. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 165 | ||
| source / vignettes | OK | 185 | ||
| linux-release | OK | 161 | ||
| macos-release | OK | 206 | ||
| macos-oldrel | OK | 171 | ||
| windows-devel | OK | 103 | ||
| windows-release | OK | 102 | ||
| windows-oldrel | OK | 84 | ||
| wasm-release | OK | 115 |
Exports:AUCcheck.matchcreateFoldscv.glmnet2cv.MTPScv.multiFitglm1glmnet.lassoglmnet.ridgeglmnet1KNN1lda1list.learnerslm1max_finitemin_finitemodify.parameterMTPSmultiFitpredict.cv.multiFitpredict.MTPSpredict.multiFitpredict.rs.multiFitqda1resid.binrpart1rs.multiFitsvm1trapezoid
Dependencies:classcodetoolse1071foreachglmnetiteratorslatticeMASSMatrixproxyRcppRcppEigenrpartshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Area Under Curve | AUC |
| Evaluation using Cross-Validation | cv.MTPS |
| HIV Drug Resistance Database | HIV XX YY |
| Internal Data Object | ctn.plot.data mix.plot.data mse.data pred.mix.rs pred.prs.std y.test.bin y.test.mix |
| List Available Base Learners | glm1 glmnet.lasso glmnet.ridge glmnet1 KNN1 lda1 list.learners lm1 qda1 rpart1 svm1 |
| Modify Default Parameters For Base Learner | modify.parameter |
| Fit Models using Revised Stacking Algorithm | MTPS |
| Fit models on multiple outcomes | multiFit |
| Make predictions from a "MTPS" model | predict.MTPS |
| Make predictions for multiple outcomes | predict.multiFit |