CANF: Clustering and anomaly detection method using nearest and farthest neighbor
A Faroughi, R Javidan - Future Generation Computer Systems, 2018 - Elsevier
Nearest-neighbor density estimators usually do not work well for high dimensional datasets.
Moreover, they have high time complexity of O (n 2) and require high memory usage …
Moreover, they have high time complexity of O (n 2) and require high memory usage …
Offline and online density estimation for large high-dimensional data
A Majdara - 2018 - search.proquest.com
Density estimation has wide applications in machine learning and data analysis techniques
including clustering, classification, multimodality analysis, bump hunting and anomaly …
including clustering, classification, multimodality analysis, bump hunting and anomaly …
A Reduced KELM model using DBSCAN Clustering algorithm for centroid selection
S Jain, S Shukla - 2018 5th International Conference on Signal …, 2018 - ieeexplore.ieee.org
Extreme Learning Machine (ELM) is a single layer feedforward neural network (SLFN) and a
popular classifier for classification and regression problems. It is unstable due to random …
popular classifier for classification and regression problems. It is unstable due to random …
[PDF][PDF] A Novel Density based Clustering Method using Nearest and Farthest Neighbor with PCA
A Faroughi, R Javidan - International Journal of Information & …, 2017 - ijict.itrc.ac.ir
Paper Title (use style: paper title) Page 1 A Novel Density based Clustering Method using
Nearest and Farthest Neighbor with PCA Azadeh Faroughi Computer Engineering and IT …
Nearest and Farthest Neighbor with PCA Azadeh Faroughi Computer Engineering and IT …
[引用][C] Density Based Spatial Clustering Application with Noise by Varying Densities
V Neerugatti, RMRA MokkalaKiranMoni - International Journal of Recent Technology and …