Essays about: "multivariate time-series data"

Showing result 11 - 15 of 87 essays containing the words multivariate time-series data.

1. 11. An empirical study of the impact of data dimensionality on the performance of change point detection algorithms

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Léo Noharet; [2023]
   Keywords : Time series segmentation; Change point detection; Multivariate time series; Data dimensionality; Tidsserie-segmentering; Förändringspunkts detektering; Mulitvariabla tidsserier; Data dimentionalitet;

   Abstract : When a system is monitored over time, changes can be discovered in the time series of monitored variables. Change Point Detection (CPD) aims at finding the time point where a change occurs in the monitored system. READ MORE

3. 12. Finding Causal Relationships Among Metrics In A Cloud-Native Environment

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Suresh Rishi Nandan; [2023]
   Keywords : Causality; Causal Discovery; Bayesian Network; Conditional Independence; Partial Correlation; Ensemble Causal Discovery; Anomaly Detection; Causal Graphs; Causality; Causal Discovery; Bayesian Network; Conditional Indeberoende; partiell korrelation; Ensemble Causal Discovery; Anomali Detektion; kausala grafer;

   Abstract : Automatic Root Cause Analysis (RCA) systems aim to streamline the process of identifying the underlying cause of software failures in complex cloud-native environments. These systems employ graph-like structures to represent causal relationships between different components of a software application. READ MORE

4. 13. A Transformer-Based Scoring Approach for Startup Success Prediction : Utilizing Deep Learning Architectures and Multivariate Time Series Classification to Predict Successful Companies

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Gustaf Halvardsson; [2023]
   Keywords : Machine learning; Time Series Classification; Transformers; Gated Recurrent Unit; Venture Capital; Maskininlärning; tidsseriesklassifiering; Transformer; Gated Recurrent Unit; riskkapital;

   Abstract : The Transformer, an attention-based deep learning architecture, has shown promising capabilities in both Natural Language Processing and Computer Vision. Recently, it has also been applied to time series classification, which has traditionally used statistical methods or the Gated Recurrent Unit (GRU). READ MORE

5. 14. Evaluating clustering techniques in financial time series

   University essay from Uppsala universitet/Avdelningen för systemteknik

   Author : Johan Millberg; [2023]
   Keywords : clustering; machine learning; financial time series; time series; unsupervised learning; cluster validation; cluster evaluation; klustring; klusteranalys; finansiella tidsserier; maskininlärning; klustervalidering; evalueringsteknik;

   Abstract : This degree project aims to investigate different evaluation strategies for clustering methodsused to cluster multivariate financial time series. Clustering is a type of data mining techniquewith the purpose of partitioning a data set based on similarity to data points in the same cluster,and dissimilarity to data points in other clusters. READ MORE

6. 15. A Deep Learning approach to Analysing Multimodal User Feedback during Adaptive Robot-Human Presentations : A comparative study of state-of-the-art Deep Learning architectures against high performing Machine Learning approaches

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Manuel Fraile Rodríguez; [2023]
   Keywords : Human Feedback; Deep Learning; Convolutional Neural Networks; Transformers; Mänsklig återmatning; mänsklig feedback; djupinlärning; CNN; transformer;

   Abstract : When two human beings engage in a conversation, feedback is generally present since it helps in modulating and guiding the conversation for the involved parties. When a robotic agent engages in a conversation with a human, the robot is not capable of understanding the feedback given by the human as other humans would. READ MORE