Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach

Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach

Predicting innovation outcomes at the firm level continues to be an important but challenging goal for researchers and practitioners alike. In this study, multiple machine learning models, encompassing both ensemble-based and single-model approaches, were applied to data from the Community Innovatio...

Full description

Saved in:
Bibliographic Details
Main Authors: Marko Martinović, Kristian Dokic, Dalibor Pudić
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
innovation prediction
machine learning
ensemble methods
cross-validation
classification performance
computational efficiency
Online Access:https://www.mdpi.com/2076-3417/15/7/3636
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2076-3417/15/7/3636

Similar Items