Sökning: "numeriska och kategoriska tidsserier"
Hittade 3 uppsatser innehållade orden numeriska och kategoriska tidsserier.
1. Detecting Faults in Telecom Software Using Diffusion Models : A proof of concept study for the application of diffusion models on Telecom data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis focuses on software fault detection in the telecom industry, which is crucial for companies like Ericsson to ensure stable and reliable software. Given the importance of software performance to companies that rely on it, automatically detecting faulty behavior in test or operational environments is challenging. LÄS MER
2. Clustering of Unevenly Spaced Mixed Data Time Series
Master-uppsats, KTH/Matematisk statistikSammanfattning : This thesis explores the feasibility of clustering mixed data and unevenly spaced time series for customer segmentation. The proposed method implements the Gower dissimilarity as the local distance function in dynamic time warping to calculate dissimilarities between mixed data time series. LÄS MER
3. Detecting Performance Anomalies in a Mobile Application with Unsupervised Machine Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Unsupervised anomaly detection algorithms are applied with the purpose of identifying performance regressions in a mobile application. To evaluate the performance, a labeled artificial data set is generated that is based on a real data set and that aims to reflect its properties. LÄS MER