# Retraction Note: ensemble learning with recursive feature elimination integrated software effort estimation: a novel approach

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/retraction-note-ensemble-learning-with-recursive-feature-elimination-integrated/

## Facts

| Field | Value |
| --- | --- |
| Author Names | K. Eswara Rao,G. Appa Rao |
| Citations | 2 |
| DOI | 10.1007/s12065-022-00785-0 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://link.springer.com/content/pdf/10.1007/s12065-022-00785-0.pdf |
| OpenAlex ID | https://openalex.org/W4304591329 |
| Type | retraction |
| Year | 2022 |

## Paper authors

- [K. Eswara Rao](https://scholariq.org/researchers/k-eswara-rao/)

## Paper primary topic

- [Software Engineering Research](https://scholariq.org/topics/software-engineering-research/)

## Paper topics

- [Software Engineering Research](https://scholariq.org/topics/software-engineering-research/)
- [Software Reliability and Analysis Research](https://scholariq.org/topics/software-reliability-and-analysis-research/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.