Data Pattern Analysis


Research lines:

  • Active, inductive and transductive learning
  • Anomaly / outlier detection
  • Bioinformatics
  • Complex networks
  • Data cluster analysis (clustering)
  • Data mining: structured, unstructured and mixed data
  • Data mining: unsupervised, semi-supervised and supervised
  • Data preparation:imputation, feature selection, dimensionality reduction, etc.
  • Data streams mining
  • Ensembles: classifiers, clusterings and outlier detectors
  • Graph and text mining
  • Machine learning: unsupervised, semi-supervised and supervised
  • Nonlinear regression
  • One class learning
  • Parallel and distributed data mining
  • Pattern classification
  • Recommender systems
  • Social network analysis
  • Statistical learning: Bayesian methods
  • Transfer learning

Data Patern Analysis
Data Pattern Analysis laboratory
 

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