Clustering Algorithms Evaluation
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Benchmarks
Fashion-MNIST
MNIST
Olivetti face
97 synthetic datasets
JAFFE
ionosphere
iris
pathbased
pixraw10P
seeds
Most implemented
Git: Clustering Based on Graph of Intensity Topology
CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering
Autoencoder Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm
The Area Under the ROC Curve as a Measure of Clustering Quality
Papers
CSTS: A Benchmark for the Discovery of Correlation Structures in Time Series Clustering
Time series clustering promises to uncover hidden structural patterns in data with applications across healthcare, finance, industrial systems, and other critical domains. However, without validated ground truth informat…
ClusteringClustering Algorithms EvaluationClustering Multivariate Time SeriesTime Series+1Autoencoder Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm
This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become more …
ClusteringClustering Algorithms EvaluationClustering Multivariate Time SeriesTime Series+1Git: Clustering Based on Graph of Intensity Topology
\textbf{A}ccuracy, \textbf{R}obustness to noises and scales, \textbf{I}nterpretability, \textbf{S}peed, and \textbf{E}asy to use (ARISE) are crucial requirements of a good clustering algorithm. However, achieving these g…
ClusteringClustering Algorithms EvaluationThe Area Under the ROC Curve as a Measure of Clustering Quality
The Area Under the the Receiver Operating Characteristics (ROC) Curve, referred to as AUC, is a well-known performance measure in the supervised learning domain. Due to its compelling features, it has been employed in a …
ClusteringClustering Algorithms EvaluationAn Internal Cluster Validity Index Using a Distance-based Separability Measure
To evaluate clustering results is a significant part of cluster analysis. There are no true class labels for clustering in typical unsupervised learning. Thus, a number of internal evaluations, which use predicted labels…
ClusteringClustering Algorithms EvaluationA predictive model for the identification of learning styles in MOOC environments
Massive online open course (MOOC) platform generates a large amount of data, which provides many opportunities for studying the behaviors of learners. In parallel, recent advancements in machine learning techniques and b…
Anomaly DetectionAutomatic Machine Learning Model SelectionClustering Algorithms EvaluationEvent data classification