Sökning: "partitioning"
Visar resultat 1 - 5 av 219 uppsatser innehållade ordet partitioning.
1. Domain Knowledge and Representation Learning for Centroid Initialization in Text Clustering with k-Means : An exploratory study
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Text clustering is a problem where texts are partitioned into homogeneous clusters, such as partitioning them based on their sentiment value. Two techniques to address the problem are representation learning, in particular language representation models, and clustering algorithms. LÄS MER
2. Complexity Analysis and Structural Optimization for Architecture Models of Mechatronic Systems
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : The design and development of mechatronic system are becoming an increasingly complex task due to the numerous disciplines involved, rapidly increasing scales, and the integration issues of different domains and technologies. The structural complexity of the architecture model design decides the quality of system design in many aspects: the scalability of the system design; usage of allocated resources which influences the computational overhead, etc. LÄS MER
3. Unsupervised Clustering of Behavior Data From a Parking Application : A Heuristic and Deep Learning Approach
Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : This report aims to present a project in the field of unsupervised clustering on human behavior in a parking application. With increasing opportunities to collect and store data, the demands to utilize the data in meaningful ways also increase. LÄS MER
4. Reducing costs of manual regression testing using prioritisation and partitioning techniques
Master-uppsats, Lunds universitet/Institutionen för datavetenskapSammanfattning : .... LÄS MER
5. Scalable Nonparametric L1 Density Estimation via Sparse Subtree Partitioning
Master-uppsats, Uppsala universitet/Statistik, AI och data scienceSammanfattning : We consider the construction of multivariate histogram estimators for any density f seeking to minimize its L1 distance to the true underlying density using arbitrarily large sample sizes. Theory for such estimators exist and the early stages of distributed implementations are available. LÄS MER