Class Density

Class density, referring to the concentration of data points within each class of a dataset, is a crucial factor influencing the performance of machine learning models, particularly in scenarios with imbalanced class distributions. Current research focuses on developing methods to accurately estimate and leverage class density information, employing techniques like probabilistic neural networks with skewed kernels and spectral clustering algorithms, to improve model training and prediction accuracy. This research is significant because addressing class density issues directly enhances the reliability and generalizability of machine learning models across various applications, including medical risk prediction and anomaly detection, leading to more robust and accurate results.

Papers

December 10, 2023

Skew Probabilistic Neural Networks for Learning from Imbalanced Data
Shraddha M. Naik, Tanujit Chakraborty, Abdenour Hadid, Bibhas Chakraborty
Imbalanced Data Imbalanced Datasets Imbalanced Classification Probabilistic Neural Network Class Density

May 11, 2023

Spectral Clustering on Large Datasets: When Does it Work? Theory from Continuous Clustering and Density Cheeger-Buser
Timothy Chu, Gary Miller, Noel Walkington
Theoretical Understanding Spectral Clustering Clustering Algorithm Large Datasets Spectral Filtering Class Density

December 5, 2022

Indoor room Occupancy Counting based on LSTM and Environmental Sensor
Zheyu Zhang
Deep Learning Machine Learning Long Short Term Memory LSTM Network State Occupancy Matching Environmental Sensor Class Density

July 23, 2022

Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data
Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi
Training Model Risk Prediction Medical Datasets Aware Loss Imbalanced Medical Class Density

February 8, 2022

Class Density and Dataset Quality in High-Dimensional, Unstructured Data
Adam Byerly, Tatiana Kalganova
High Dimension Unstructured Data Unstructured Text Data Dataset Quality Class Density

Class Density

Papers

Skew Probabilistic Neural Networks for Learning from Imbalanced Data

Spectral Clustering on Large Datasets: When Does it Work? Theory from Continuous Clustering and Density Cheeger-Buser

Indoor room Occupancy Counting based on LSTM and Environmental Sensor

Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data

Class Density and Dataset Quality in High-Dimensional, Unstructured Data