iimi
1.2.2Identifying Infection with Machine Intelligence
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4.2Kdownloads / year
–test coverage
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Overview
About
A novel machine learning method for plant viruses diagnostic using genome sequencing data. This package includes three different machine learning models, random forest, XGBoost, and elastic net, to train and predict mapped genome samples. Mappability profile and unreliable regions are introduced to the algorithm, and users can build a mappability profile from scratch with functions included in the package. Plotting mapped sample coverage information is provided.
Install
Health
CRAN checks
13OK
Slowest check: 12.0 min · r-devel-linux-x86_64-fedora-clang
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
15
Dependencies · direct
Check history
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-1013 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-05-0312 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-0213 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- ERROR2026-04-2511 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
- Examples that run
- 14%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
4.2K
CRAN downloads in the past year
Rank #18,156 · ~11/day · ~349/mo
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20230 days
65090 days
4.2K1 year
Also on141 r2u
Dependencies
Declared dependencies
18 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
Imports (15)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect
Nothing depends on this yet.
Code & Tests
Datasets
People & History
People (6)
Maintainer (1)
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Authors (6)
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Package Timeline
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Package metadata
- First published
- 2024-03-07
- Total releases
- 5 / 2 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 2.4 MB / 7 files
- Download size
- 2.5 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet