The benefits of using multi-objectivization for mining pittsburgh partial classification rules in imbalanced and discrete data.
Julie JacquesJulien TaillardDavid DelerueLaetitia JourdanClarisse DhaenensPublished in: GECCO (2013)
Keyphrases
- classification rules
- discrete data
- continuous data
- decision trees
- genetic programming
- continuous attributes
- association rules
- subgroup discovery
- rule discovery
- classification algorithm
- high dimensional
- weighted graph
- data mining
- rule extraction
- rule sets
- nearest neighbor
- association rule mining
- frequent patterns
- frequent itemsets
- itemsets
- text mining
- latent dirichlet allocation
- knowledge discovery
- data mining algorithms
- pattern recognition
- similarity measure
- neural network
- knn
- genetic algorithm