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1st International Summer School on Classification and Data Analysis

The “Clustering and Classification” summer school – organised by the CLADAG (the classification group of the Italian Statistical Society) – is designed to introduce clustering and classification methods to advanced undergraduate students, PhD students and postdoctoral researchers. The Summer School is structured in theoretical lessons, tutorials and invited talks on specific themes. Each day will consist on theoretical lectures in the morning, and interactive discussions, scientific seminars and tutorials in the afternoon.
When 22 May 2017
from 07:45 PM to 07:45 PM
Where Rimini IT
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Supervised classification:

  • Bayes Classifier 
  • Linear Discriminant Analysis (LDA) 
  • Logistic Regression 
  • k-Nearest-Neighbours Classification 
  • Resampling Methods and Estimation of Misclassification Error and Area Under the Curve (AUC) 
  • Tree-based Classifiers 
  • Feature Selection Methods 
  • Ensemble Methods: Bagging, Random Forest and Boosting 
  • Selected Ensembles: Node Harvest and Optimal Trees Ensembles 
  • Random projection ensemble classification 
  • Neural Networks and Deep Learning 

 

 

Clustering/Non-supervised classification: 

  • Partitioning, fuzzy, and hierarchical clustering approaches 
  • Similarity and dissimilarity measures 
  • Basic and empirical methods 
  • Model-based clustering: Fixed partition model, mixture model, maximum likelihood approach 
  • k-means algorithm, EM-algorithm and extensions 
  • Evaluation and validation models, Pareto solutions 
  • Two-way/multi-way classification 
  • Clustering with dimension reduction, factorial cluster analysis 
  • Special cases: contingency tables, time series, document clustering, symbolic data 

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