Machine Learning
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
A streaming ensemble algorithm (SEA) for large-scale classification
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Introduction to Algorithms
Machine Learning
Probabilistic Estimation-Based Data Mining for Discovering Insurance Risks
IEEE Intelligent Systems
An introduction to variable and feature selection
The Journal of Machine Learning Research
Hybrid Genetic Algorithms for Feature Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
IEEE Intelligent Systems
Accurate Cancer Classification Using Expressions of Very Few Genes
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A Projection Pursuit Algorithm for Exploratory Data Analysis
IEEE Transactions on Computers
Multiclass MTS for Simultaneous Feature Selection and Classification
IEEE Transactions on Knowledge and Data Engineering
Correlation maximisation-based discretisation for supervised classification
International Journal of Business Intelligence and Data Mining
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In many jurisdictions, automobile insurers have access to risk-sharing pools to which they can transfer some risks. We consider different feature selection and modelling approaches to maximise profitability of these transfers through better risk selection. For that purpose, we introduce a flexible scoring model and devise a robust feature synthesis and selection method. We show what should be the most suitable sorting criterion depending on pool regulations. We use a technique, similar to cross validation, but that is coherent with the sequential structure of insurance data. We explain how software maturity level impacts profitability.