Sökning: "Tony Lindgren"
Visar resultat 1 - 5 av 6 avhandlingar innehållade orden Tony Lindgren.
1. Methods of solving conflicts among induced rules
Sammanfattning : When applying an unordered set of classification rules to classify an example, there may be several applicable rules with conflicting conclusions regarding the most probable class to which the example belongs. This problem of having rules assigning different classes to the same example must be addressed, if a classification is to be made. LÄS MER
2. Towards a Capability Model for Release Planning of Software Intensive Systems
Sammanfattning : Release planning is an early product development activity concerned with deciding which features and quality improvements that should be pursued in product development projects, i.e., it is an activity which in large parts decide how the development budget of a company is allocated. LÄS MER
3. Learning Decision Trees and Random Forests from Histogram Data : An application to component failure prediction for heavy duty trucks
Sammanfattning : A large volume of data has become commonplace in many domains these days. Machine learning algorithms can be trained to look for any useful hidden patterns in such data. Sometimes, these big data might need to be summarized to make them into a manageable size, for example by using histograms, for various reasons. LÄS MER
4. Random Forest for Histogram Data : An application in data-driven prognostic models for heavy-duty trucks
Sammanfattning : Data mining and machine learning algorithms are trained on large datasets to find useful hidden patterns. These patterns can help to gain new insights and make accurate predictions. Usually, the training data is structured in a tabular format, where the rows represent the training instances and the columns represent the features of these instances. LÄS MER
5. Z-Series : Mining and learning from complex sequential data
Sammanfattning : The amount and complexity of sequential data collected across various domains have grown rapidly, posing significant challenges for extracting useful knowledge from such data sources. The complexity arises from diverse sequence representations with varying granularities, such as multivariate time series, histogram snapshots, and heterogeneous health records, which often describe a single data instance with multiple sequences. LÄS MER