C4.5: programs for machine learning
C4.5: programs for machine learning
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Making large-scale support vector machine learning practical
Advances in kernel methods
Database-friendly random projections
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Random projection in dimensionality reduction: applications to image and text data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Derandomized dimensionality reduction with applications
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic multidimensional histograms
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Experiments with Random Projection
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Learning Mixtures of Gaussians
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
A multinomial clustering model for fast simulation of computer architecture designs
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Automatic basis function construction for approximate dynamic programming and reinforcement learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Very sparse random projections
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Very sparse stable random projections for dimension reduction in lα (0
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Kernel Perceptrons on Noisy Data Using Random Projections
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Client-Friendly Classification over Random Hyperplane Hashes
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Kernel-Based Nonparametric Regression Method
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Fast Spectral Clustering with Random Projection and Sampling
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Feature selection via Boolean independent component analysis
Information Sciences: an International Journal
Image categorization combining neighborhood methods and boosting
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Visual integration tool for heterogeneous data type by unified vectorization
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Classification of microarrays with kNN: comparison of dimensionality reduction methods
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Random projections for face detection under resource constraints
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Compressed fisher linear discriminant analysis: classification of randomly projected data
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Robust classifiers for data reduced via random projections
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fast Algorithms for Approximating the Singular Value Decomposition
ACM Transactions on Knowledge Discovery from Data (TKDD)
Clustering and semantics preservation in cultural heritage information spaces
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Random projections for SVM ensembles
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Random projections for linear SVM ensembles
Applied Intelligence
Hybrid parallel classifiers for semantic subspace learning
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Improving random projections using marginal information
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Finding uninformative features in binary data
IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
The impact of feature extraction on the performance of a classifier: kNN, Naïve Bayes and C4.5
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces
Pattern Recognition Letters
Random projection, margins, kernels, and feature-selection
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
Randomized Algorithms for Matrices and Data
Foundations and Trends® in Machine Learning
A fast subspace text categorization method using parallel classifiers
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II
Approximate privacy-preserving data mining on vertically partitioned data
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
Distributed high dimensional information theoretical image registration via random projections
Digital Signal Processing
Hybrid random subsample classifier ensemble for high dimensional data sets
International Journal of Hybrid Intelligent Systems
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Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computational advantages. In this paper we report a number of experiments to evaluate Random Projections in the context of inductive supervised learning. In particular, we compare Random Projections and PCA on a number of different datasets and using different machine learning methods. While we find that the random projection approach predictively underperforms PCA, its computational advantages may make it attractive for certain applications.