Sökning: "Imbalanced Data"
Visar resultat 1 - 5 av 80 uppsatser innehållade orden Imbalanced Data.
1. Machine Learning for Classification of Temperature Controlled Containers Using Heavily Imbalanced Data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Temperature controllable containers are used frequently in order to transport pharmaceutical cargo all around the world. One of the leading manufacturing companies of these containers has a method for detecting containers with a faulty cooling system before making a shipment. LÄS MER
2. Facilitating quality management through data mining
Master-uppsats, Mälardalens universitet/Innovation och produktrealiseringSammanfattning : In this report, the topics of quality management, knowledge work, and Lean Six Sigma areexplored with the objective of identifying potential improvements that could be facilitated byData mining methods. With the purpose of exploring the topic of knowledge extraction fromfree-text data to support decision-making in manufacturing operations from a qualitymanagement perspective. LÄS MER
3. Combining Register Data and X-Ray Images for a Precision Medicine Prediction Model of Thigh Bone Fractures
Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknikSammanfattning : The purpose of this master thesis was to investigate if using both X-ray images and patient's register data could increase the performance of a neural network in discrimination of two types of fractures in the thigh bone, called atypical femoral fractures (AFF) and normal femoral fractures (NFF). We also examined and evaluated how the fusion of the two data types could be done and how different types of fusion affect the performance. LÄS MER
4. Modification of the RusBoost algorithm : A comparison of classifiers on imbalanced data
Magister-uppsats, Umeå universitet/StatistikSammanfattning : In many situations data is imbalanced, meaning the proportion of one class is larger than the other(s). Standard classifiers often produce undesirable results when the data is imbalanced and different methods have been developed in the attempt to improve classification under such conditions. LÄS MER
5. Deep Learning Semantic Segmentation of 3D Point Cloud Data from a Photon Counting LiDAR
Master-uppsats, Linköpings universitet/DatorseendeSammanfattning : Deep learning has shown to be successful on the task of semantic segmentation of three-dimensional (3D) point clouds, which has many interesting use cases in areas such as autonomous driving and defense applications. A common type of sensor used for collecting 3D point cloud data is Light Detection and Ranging (LiDAR) sensors. LÄS MER
