Data Mining and Neural Networks

Module code: MA4022

This module will provide a comprehensive introduction to the structure of the data mining process and explain the basic notions and operation. During this module you will familiarise yourself with types of data mining problems and select the necessary approach to its solutions, from evaluation and cleaning of the dataset to selection of the algorithms for data analysis. This module will also cover the basic methods and algorithms for data analysis, and how to construct basic neural networks for data analysis. This module will focus on data analysis for classification kNN and decision tree algorithms, hierarchical clustering and density based algorithms, and demonstrate how to construct basic neural networks for data analysis (Hopfield, Kohonen, cascade correlation and backpropagation of errors).

Topics covered

  • Data pre-processing
  • Data cleaning. 
  • Dimensionality reduction, 
  • Clustering
  • Regression,
  • Probability distribution estimation
  • Time series
  • Hierarchical clustering and density based algorithms,  
  • Bayes networks,
  • Principle component analysis

Learning

  • 33 hours of lectures
  • 11 hours of tutorials
  • 5 hours of project supervision
  • 11 hours of practical classes and workshops
  • 90 hours of guided independent study

Assessment

  • Coursework (20%)
  • Computational Project (30%)
  • Exam, 2 hours (50%)