Can We Predict Types of Code Changes? An Empirical Analysis

Preprint of paper published in: 9th IEEE Working Conference on Mining Software Repositories (MSR), 2-3 June 2012; doi:10.1109/MSR.2012.6224284 There exist many approaches that help in pointing developers to the change-prone parts of a software system. Although beneficial, they mostly fall short in providing details of these changes. Fine-grained...

Sample reusability in importance-weighted active learning

Recent advances in importance-weighted active learning solve many of the problems of traditional active learning strategies. But does importance-weighted active learning also produce a reusable sample selection? This thesis explains why reusability can be a problem, how importance-weighted active learning removes some of the barriers to...

Evaluating the Quality of Opponent Models in Automated Bilateral Negotiations

Automated negotiation agents are agents that interact in an environment for the settlement of a mutual concern. An important factor influencing the performance of a negotiation agent is how it takes the opponent into account. The main challenge in this aspect, is that opponents typically hide private information to avoid exploitation. In such a...

Towards a roadmap for development of intelligent data analysis based cyber attack detection systems

Cyber-attacks against companies and governments are seeing an increase in complexity and persistence. These more complex attacks are aimed at penetrating corporate and government networks to obtain classified information. Common intrusion detection methods lack in their ability to detect such complex attacks. A framework is proposed to relate...

Finding cancer genes in copy number data and insertional mutagenesis data

Cancer is a genetic disease. Step-wise alteration of genes that have a normal function in the cell can lead to the transformation of a healthy cell into a malignant cancer cell. Cancer genes provide several traits to the cell that allow it to become malignant. These traits have been researched for many years, and currently one knows quite well...

Personalised Access to Social Media

On many websites users can personally contribute information, ranging from short text messages to photos and videos. Users can see the information contributed by others and respond to it. These social media actively engage their community in the structuring of the collection by making use of collaborative annotation methods. Next to an improved...

Ant Colony Optimization for Control

The very basis of this thesis is the collective behavior of ants in colonies. Ants are an excellent example of how rather simple behavior on a local level can lead to complex behavior on a global level that is beneficial for the individuals. The key in the self-organization of ants is communication through pheromones. When an ant forages for...

Efficient Identification of Timed Automata: Theory and practice

This thesis contains a study in a subfield of artificial intelligence, learning theory, machine learning, and statistics, known as system (or language) identification. System identification is concerned with constructing (mathematical) models from observations. Such a model is an intuitive description of a complex system. One of the main nice...

A learning Dempster-Shafer model for automated building detection

This paper presents a learning Dempster-Shafer model for the detection of buildings in aerial image and range data. The process of evidence assignment in the Dempster-Shafer method is implemented through membership functions in an adaptive network-based fuzzy inference system, where a back propagation learning rule is employed to tune the...

Efficient Multiclass ROC Approximation by Decomposition via Confusion Matrix Perturbation Analysis

Receiver operator characteristic (ROC) analysis has become a standard tool in the design and evaluation of two-class classification problems. It allows for an analysis that incorporates all possible priors, costs, and operating points, which is important in many real problems, where conditions are often nonideal. Extending this to the multiclass...

Learning to recognise: A study on one-class classification and active learning

The thesis treats classification problems which are undersampled or where there exist an unbalance between classes in the sampling. The thesis is divided into three parts. The first two parts treat the problem of one-class classification. In the one-class classification problem, it is assumed that only examples of one of the classes, the target...

Fuzzy Probabilistic Learning and Reasoning, Rule Induction for Decision-Support Systems in Exacting Environments