[HTML][HTML] Optimizing Parkinson's Disease Prediction: A Comparative Analysis of Data Aggregation Methods Using Multiple Voice Recordings via an Automated Artificial …
Z Yang, H Zhou, S Srivastav, JG Shaffer, KE Abraham… - Data, 2025 - mdpi.com
Patient-level grouped data are prevalent in public health and medical fields, and multiple
instance learning (MIL) offers a framework to address the challenges associated with this …
instance learning (MIL) offers a framework to address the challenges associated with this …
[HTML][HTML] MIPART: A Partial Decision Tree-Based Method for Multiple-Instance Classification
KF Balbal - Applied Sciences, 2024 - mdpi.com
Multi-instance learning (MIL) is a critical area in machine learning, particularly for
applications where data points are grouped into bags. Traditional methods, however, often …
applications where data points are grouped into bags. Traditional methods, however, often …
[PDF][PDF] CORRELATION-BASED FEATURE SELECTION WITH BAG-BASED FUSION SCHEME FOR MULTI-INSTANCE LEARNING APPLICATION
M BERAHIM, NA SAMSUDIN… - Journal of Engineering …, 2022 - researchgate.net
Abstract Multi-Instance Learning (MIL) classifies a bag of instances rather than an individual
instance. There is a lack of consideration of feature selection in MIL. The large number of …
instance. There is a lack of consideration of feature selection in MIL. The large number of …
Bag-Based Feature-Class Correlation Analysis for Multi-Instance Learning Application
Multi-instance Learning (MIL) is widely applied in image classification. In MIL, an image is
presented as a bag. A bag consists of multi-instance which is known as patches. Irrelevant …
presented as a bag. A bag consists of multi-instance which is known as patches. Irrelevant …