---
title: Cluster Analysis for Missing Values
url: https://www.ml-quant.com/papers/repec/anm-alpnmr-v-9-y-2021-i-2-p-299-310/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:anm:alpnmr:v:9:y:2021:i:2:p:299-310
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.alphanumericjournal.com%2Fmedia%2FIssue%2Fvolume-9-issue-2-2021%2Fa-proposal-method-for-missing-value-analysis-cluster-analysi_eYwJjXT.pdf%3Bh%3Drepec%3Aanm%3Aalpnmr%3Av%3A9%3Ay%3A2021%3Ai%3A2%3Ap%3A299-310
featured: 2023-08-24
citations: unknown
topic: Other
---


# Cluster Analysis for Missing Values

The study shows that clustering analysis effectively imputes more representative values in missing data cases, ensuring the data structure remains intact.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.alphanumericjournal.com%2Fmedia%2FIssue%2Fvolume-9-issue-2-2021%2Fa-proposal-method-for-missing-value-analysis-cluster-analysi_eYwJjXT.pdf%3Bh%3Drepec%3Aanm%3Aalpnmr%3Av%3A9%3Ay%3A2021%3Ai%3A2%3Ap%3A299-310
- Identifier: RePEc:anm:alpnmr:v:9:y:2021:i:2:p:299-310
- Released: 2021-02-18
- First featured: Quant Letter No. 13 (2023-08-24): https://www.ml-quant.com/issues/2023-08-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Other

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