Sökning: "Time To Event prediction"

Visar resultat 1 - 5 av 56 uppsatser innehållade orden Time To Event prediction.

  1. 1. Detecting Fraudulent User Behaviour : A Study of User Behaviour and Machine Learning in Fraud Detection

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Analys och partiella differentialekvationer

    Författare :Patrik Gerdelius; Sjönneby Hugo; [2024]
    Nyckelord :Fraud Detection; User Behaviour; Random Forest; PCA; SMOTE;

    Sammanfattning : This study aims to create a Machine Learning model and investigate its performance of detecting fraudulent user behaviour on an e-commerce platform. The user data was analysed to identify and extract critical features distinguishing regular users from fraudulent users. LÄS MER

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

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Luca Colasanti; [2023]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  4. 3. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Yuxin Sun; [2023]
    Nyckelord :LSTM; Anomaly Detection; Failure Prediction; Log Mining; Deep Learning; LSTM; Anomali Detection; Failure Prediction; Log Mining; Deep Learning;

    Sammanfattning : Since many log tracing application and diagnostic commands are now available on nodes at base station, event log can easily be collected, parsed and structured for network performance analysis. In order to improve In Service Performance of customer network, a sequential machine learning model can be trained, test, and deployed on each node to learn from the past events to predict future crashes or a failure. LÄS MER

  5. 4. MODELING INPUT VARIABLE AGE IN SEPSIS PREDICTION USING TREE-BASED MODELS

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Oscar Wastesson; [2023]
    Nyckelord :Machine learning; decision trees; sepsis; classification;

    Sammanfattning : Last observation carried forward (LOCF) is a common imputation method, regularly used for clinical data. It is based on the principle that the most recent observation that is known is carried forward to replace missing values. LÄS MER

  7. 5. WSA-ENLIL + Cone ensemble modeling of an Earth-directed ICME : Comparison with in-situ observations by Solar Orbiter and WIND at L1

    Master-uppsats, Uppsala universitet/Institutionen för fysik och astronomi; Uppsala universitet/Institutet för rymdfysik, Uppsalaavdelningen

    Författare :Alberto García Ribas; [2023]
    Nyckelord :;

    Sammanfattning : Coronal mass ejections (CMEs) are considered the most energetic phenomenon in the heliosphere. Originated in the solar corona, they are formed by ejected plasma driven by strong magnetic fields. LÄS MER