Essays about: "Recurrent event data"

Showing result 1 - 5 of 20 essays containing the words Recurrent event data.

  1. 1. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

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

    Author : Luca Colasanti; [2023]
    Keywords : Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

    Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE

  3. 2. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis

    University essay from KTH/Matematik (Avd.)

    Author : Nazar Maksymchuk Netterström; [2023]
    Keywords : Recurrent Neural Network; Long-Short-Term-Memory; Topological Data Analysis; Session based data; Anomaly detection; Time-series analysis; Imbalanced data; Master thesis; Neurala nätverk; Topologisk data analys; Detektion av avvikelse; Sessionsbaserad data; Tidserieanalys; Inbalancerad data; Masteruppsats;

    Abstract : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. READ MORE

  4. 3. Event-Based Visual SLAM : An Explorative Approach

    University essay from Uppsala universitet/Signaler och system

    Author : Johan Rideg; [2023]
    Keywords : event camera; neuromorphic; SLAM; visual odometry;

    Abstract : Simultaneous Localization And Mapping (SLAM) is an important topic within the field of roboticsaiming to localize an agent in a unknown or partially known environment while simultaneouslymapping the environment. The ability to perform robust SLAM is especially important inhazardous environments such as natural disasters, firefighting and space exploration wherehuman exploration may be too dangerous or impractical. READ MORE

  5. 4. Automatic event detection oncontinuous glucose datausing neural networks

    University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Author : David Borghäll; [2023]
    Keywords : Automatic Event Detection; Continuous Glucose Monitor; Deep Learning; Diabetes Mellitus; Automatisk Eventdetektion; Kontinuerlig Glukosmätare; Djupinlärning; Diabetes;

    Abstract : Automatically detecting events for people with diabetes mellitus using continuousglucose monitors is an important step in allowing insulin pumps to automaticallycorrect the blood glucose levels and for a more hands-off approach to thedisease. The automatic detection of events could also aid physicians whenassisting their patients when referring to their continuous glucose monitordata. READ MORE

  6. 5. Graph Neural Networks for Events Detection in Football

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

    Author : Giovanni Castellano; [2023]
    Keywords : Machine Learning; Graph Neural Network; Recurrent Neural Network; Trajectory Data; Football; Events Detection; Maskininlärning; Graph Neural Network; Recurrent Neural Network; Bandata; fotboll; händelsedetektering;

    Abstract : Tracab’s optical tracking system allows to track the 2-dimensional trajectories of players and ball during a football game. Using this data it is possible to train machine learning models to identify events that happen during the match. READ MORE