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A meta-heuristic density-based subspace clustering algorithm for high-dimensional data

https://doi.org/10.1007/s00500-021-05973-1

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Clustering high dimensional data

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A Comparison of Ranking Methods for Classification Algorithm Selection

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Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering

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Flower Pollination Algorithm for Global Optimization

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The Challenges of Clustering High Dimensional Data

inferredcites →https://doi.org/10.1007/s00500-018-3339-yopenalex-snapshot

Robust discriminant low-rank representation for subspace clustering

inferredcites →https://doi.org/10.1007/s00500-020-04865-0openalex-snapshot

Non-convex low-rank representation combined with rank-one matrix sum for subspace clustering

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Empirical analysis of five nature-inspired algorithms on real parameter optimization problems

inferredcites →https://doi.org/10.1007/s10898-007-9149-xopenalex-snapshot

A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm

inferredcites →https://doi.org/10.1007/s10994-009-5154-2openalex-snapshot

Particle swarm optimizer for variable weighting in clustering high-dimensional data

inferredcites →https://doi.org/10.1016/j.cma.2020.113609openalex-snapshot

The Arithmetic Optimization Algorithm

inferredcites →https://doi.org/10.1016/j.ins.2016.01.101openalex-snapshot

A survey on soft subspace clustering

inferredcites →https://doi.org/10.1016/j.jcp.2007.06.008openalex-snapshot

Lévy flights, non-local search and simulated annealing

inferredcites →https://doi.org/10.1016/j.jecp.2010.03.005openalex-snapshot

The development of spatial frequency biases in face recognition

inferredcites →https://doi.org/10.1016/j.knosys.2020.105512openalex-snapshot

Subspace clustering by simultaneously feature selection and similarity learning

inferredcites →https://doi.org/10.1016/j.patrec.2018.07.003openalex-snapshot

Subspace clustering with the multivariate-t distribution

inferredcites →https://doi.org/10.1016/j.patrec.2019.01.016openalex-snapshot

Adaptive multi-view subspace clustering for high-dimensional data

inferredcites →https://doi.org/10.1016/s0169-7439(01)00111-3openalex-snapshot

Looking for natural patterns in data

inferredcites →https://doi.org/10.1023/a:1008202821328openalex-snapshot

Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces

inferredcites →https://doi.org/10.1080/1206212x.2016.1224401openalex-snapshot

Enhanced flower pollination algorithm on data clustering

inferredcites →https://doi.org/10.1109/cec.2003.1299749openalex-snapshot

Towards effective subspace clustering with an evolutionary algorithm

inferredcites →https://doi.org/10.1109/cec.2014.6900313openalex-snapshot

A hybrid EA for high-dimensional subspace clustering problem

inferredcites →https://doi.org/10.1109/icdm.2003.1251009openalex-snapshot

Frequent-pattern based iterative projected clustering

inferredcites →https://doi.org/10.1109/icdm.2004.10099openalex-snapshot

SCHISM: A New Approach for Interesting Subspace Mining

inferredcites →https://doi.org/10.1109/icdm.2005.5openalex-snapshot

A Generic Framework for Efficient Subspace Clustering of High-Dimensional Data

inferredcites →https://doi.org/10.1109/icdm.2006.123openalex-snapshot

P3C: A Robust Projected Clustering Algorithm

inferredcites →https://doi.org/10.1109/icdm.2008.46openalex-snapshot

INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy

inferredcites →https://doi.org/10.1109/icdmw.2014.100openalex-snapshot

SUBSCALE: Fast and Scalable Subspace Clustering for High Dimensional Data

inferredcites →https://doi.org/10.1109/icrcicn.2015.7434221openalex-snapshot

Comparative analysis of nature inspired algorithms on data clustering

inferredcites →https://doi.org/10.1109/tcyb.2015.2477416openalex-snapshot

A Hybrid Approach to Clustering in Big Data

inferredcites →https://doi.org/10.1109/tetc.2014.2330519openalex-snapshot

A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis

inferredcites →https://doi.org/10.1137/1.9781611972740.23openalex-snapshot

Density-Connected Subspace Clustering for High-Dimensional Data

inferredcites →https://doi.org/10.1137/1.9781611972740.58openalex-snapshot

Subspace Clustering of High Dimensional Data

inferredcites →https://doi.org/10.1145/1007730.1007731openalex-snapshot

Subspace clustering for high dimensional data

inferredcites →https://doi.org/10.1145/1401890.1401956openalex-snapshot

Finding non-redundant, statistically significant regions in high dimensional data

inferredcites →https://doi.org/10.1145/1497577.1497578openalex-snapshot

Clustering high-dimensional data

inferredcites →https://doi.org/10.1145/276304.276314openalex-snapshot

Automatic subspace clustering of high dimensional data for data mining applications

inferredcites →https://doi.org/10.1145/276305.276314openalex-snapshot

Automatic subspace clustering of high dimensional data for data mining applications

inferredcites →https://doi.org/10.1145/304181.304188openalex-snapshot

Fast algorithms for projected clustering

inferredcites →https://doi.org/10.1145/564691.564739openalex-snapshot

A Monte Carlo algorithm for fast projective clustering

inferredcites →https://doi.org/10.1186/s40537-015-0027-yopenalex-snapshot

A novel algorithm for fast and scalable subspace clustering of high-dimensional data

inferredcites →https://doi.org/10.14778/1687627.1687770openalex-snapshot

Evaluating clustering in subspace projections of high dimensional data

inferredcites →https://doi.org/10.1504/ijbic.2018.10014476openalex-snapshot

ABC_DE_FP: A Novel Hybrid Algorithm for Complex Continuous Optimization Problems

inferredcites →https://doi.org/10.3390/a13120345openalex-snapshot

Nature-Inspired Optimization Algorithms for Text Document Clustering—A Comprehensive Analysis

inferredcites →https://doi.org/10.3390/electronics10020101openalex-snapshot

Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering

inferredcites →https://doi.org/10.3758/s13428-013-0329-yopenalex-snapshot

Subspace K-means clustering

inferredcites →https://doi.org/10.4018/978-1-5225-5852-1openalex-snapshot

Nature-Inspired Algorithms for Big Data Frameworks

inferredcites →https://doi.org/10.4018/978-1-5225-5852-1.ch003openalex-snapshot

Subspace Clustering of High Dimensional Data Using Differential Evolution

inferredcites →https://doi.org/10.5120/15890-5059openalex-snapshot

Choosing DBSCAN Parameters Automatically using Differential Evolution

inferredcites →https://doi.org/10.5120/17593-8331openalex-snapshot

Nature-Inspired Algorithms: State-of-Art, Problems and Prospects

inferredcites →https://doi.org/10.7939/r3j678z1wopenalex-snapshot

Finding non-Redundant, Statistically Significant Regions in High Dimensional Data: a Novel Approach to Projected and Subspace Clustering

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Performance Evaluation of Smart Flower Optimization Algorithm Over Industrial Non-convex Constrained Optimization Problems

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An efficient DBSCAN optimized by arithmetic optimization algorithm with opposition-based learning

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A novel two-stage bio-inspired method using red deer algorithm for data clustering

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An improved multi-population whale optimization algorithm

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An Improved Quantum Inspired Particle Swarm Optimization for Forest Cover Prediction

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Flexible multi-objective particle swarm optimization clustering with game theory to address human activity discovery fully unsupervised

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Automatic deep sparse clustering with a dynamic population-based evolutionary algorithm using reinforcement learning and transfer learning

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Principal component Gaussian optimization for enhancing metaheuristic algorithms in high-dimensional problems

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Agglomerative clustering enhanced GA for optimal seed selection in online social networks

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A Novel Skeleton-Based Human Activity Discovery Using Particle Swarm Optimization With Gaussian Mutation

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Human Activity Discovery With Automatic Multi-Objective Particle Swarm Optimization Clustering With Gaussian Mutation and Game Theory

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A New Harris Hawk Whale Optimization Algorithm for Enhancing Neural Networks

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Adaptive Hybridized Meta-Heuristic Algorithm for Subspace Clustering on High Dimensional Data

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An IoT Data Clustering Algorithm for Efficient and Cost-Effective Human Resource Assessment

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Enhanced Firefly-K-Means Clustering with Adaptive Mutation and Central Limit Theorem for Automatic Clustering of High-Dimensional Datasets

inferred← citeshttps://doi.org/10.36227/techrxiv.19633869.v1openalex-snapshot

Flexible Multi-Objective Particle Swam Optimization Clustering with Game Theory to Address Human Activity Recognition Fully Unsupervised

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Flexible Multi-Objective Particle Swarm Optimization Clustering with Game Theory to Address Human Activity Recognition Fully Unsupervised

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A Hybrid Whale Genetic Algorithm for Feature Selection in Biomedical Dataset

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A Taxonomy of DBSCAN Variants Addressing Parameter Dependence and High-Dimensionality

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