---
title: CostSensitive Machine Learning for Investments
url: https://www.ml-quant.com/papers/repec/wly-isacfm-v-31-y-2024-i-1-n-e1548/
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:wly:isacfm:v:31:y:2024:i:1:n:e1548
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Fisaf.1548%3Bh%3Drepec%3Awly%3Aisacfm%3Av%3A31%3Ay%3A2024%3Ai%3A1%3An%3Ae1548
featured: 2024-04-10
citations: unknown
topic: ML & AI Methods
---


# CostSensitive Machine Learning for Investments

The study employs cost-sensitive machine learning models to predict startup success, potentially reducing investor risk but possibly limiting gains, and proposes ways to improve successful startup detection.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1002%2Fisaf.1548%3Bh%3Drepec%3Awly%3Aisacfm%3Av%3A31%3Ay%3A2024%3Ai%3A1%3An%3Ae1548
- Identifier: RePEc:wly:isacfm:v:31:y:2024:i:1:n:e1548
- Released: 2024-04-10
- First featured: Quant Letter No. 44 (2024-04-10): https://www.ml-quant.com/issues/2024-04-10/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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