Uncertainty Based Optimal Sample Selection for Big Data

Uncertainty Based Optimal Sample Selection for Big Data

In Machine learning and pattern recognition, building a better predictive model is one of the key problems in the presence of big or massive data; especially, if that data contains noisy and unrepresentative data samples. These types of samples adversely affect the learning model and may degrade its...

Full description

Bibliographic Details
Main Authors: Saadia Ajmal, Rana Aamir Raza Ashfaq, Kashif Saleem
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Big data
instance selection
machine learning
uncertainty
Online Access:https://ieeexplore.ieee.org/document/10004968/

Similar Items

Similar Items