Sökning: "Niklas Lavesson"
Visar resultat 1 - 5 av 19 avhandlingar innehållade orden Niklas Lavesson.
1. Evaluation and Analysis of Supervised Learning Algorithms and Classifiers
Sammanfattning : The fundamental question studied in this thesis is how to evaluate and analyse supervised learning algorithms and classifiers. As a first step, we analyse current evaluation methods. Each method is described and categorised according to a number of properties. LÄS MER
2. On the Metric-based Approach to Supervised Concept Learning
Sammanfattning : A classifier is a piece of software that is able to categorize objects for which the class is unknown. The task of automatically generating classifiers by generalizing from examples is an important problem in many practical applications. This problem is often referred to as supervised concept learning, and has been shown to be relevant in e.g. LÄS MER
3. Enhancing genetic programming for predictive modeling
Sammanfattning : See separate file, "Abstract.png"... LÄS MER
4. Data Mining Approaches for Outlier Detection Analysis
Sammanfattning : Outlier detection is studied and applied in many domains. Outliers arise due to different reasons such as fraudulent activities, structural defects, health problems, and mechanical issues. The detection of outliers is a challenging task that can reveal system faults, fraud, and save people's lives. LÄS MER
5. Data Modeling for Outlier Detection
Sammanfattning : This thesis explores the data modeling for outlier detection techniques in three different application domains: maritime surveillance, district heating, and online media and sequence datasets. The proposed models are evaluated and validated under different experimental scenarios, taking into account specific characteristics and setups of the different domains. LÄS MER