Essays about: "sequential learning"

Showing result 6 - 10 of 123 essays containing the words sequential learning.

1. 6. ASSESSING PREDICTION CONDITIONS ANDSEQUENTIAL CLASSIFICATION IN ICU SEPSISPREDICTION

   University essay from Uppsala universitet/Statistiska institutionen

   Author : Petter Lind; [2023]
   Keywords : Sepsis Prediction; Sequential Prediction; Conditional Predictions; XGBoost;

   Abstract : Patients admitted to intensive care units (ICUs) often have a higher risk of sepsis due to weakened immune systems. Early sepsis diagnosis is crucial for timely treatment, emphasizing the need to improve the predictive capabilities of sepsis prediction models. READ MORE

3. 7. Detection of insurance fraud using NLP and ML

   University essay from Lunds universitet/Matematisk statistik

   Author : Rasmus Bäcklund; Hampus Öhman; [2023]
   Keywords : Technology and Engineering;

   Abstract : Machine-Learning can sometimes see things we as humans can not. In this thesis we evaluated three different Natural Language Procces-techniques: BERT, word2vec and linguistic analysis (UDPipe), on their performance in detecting insurance fraud based on transcribed audio from phone calls (referred to as audio data) and written text (referred to as text-form data), related to insurance claims. READ MORE

4. 8. 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

5. 9. AI/ML Development for RAN Applications : Deep Learning in Log Event Prediction

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

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

   Abstract : 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. READ MORE

6. 10. A Gradient Boosting Tree Approach for Behavioural Credit Scoring

   University essay from KTH/Matematisk statistik

   Author : Axel Dernsjö; Ebba Blom; [2023]
   Keywords : Machine learning; Random forest; Uncertainty measure; Material development; Empirical Bayes; Maskininlärning; Random forest; Osäkerhetsmått; Materialutveckling; Empirical Bayes;

   Abstract : This report evaluates the possibility of using sequential learning in a material development setting to help predict material properties and speed up the development of new materials. To do this a Random forest model was built incorporating carefully calibrated prediction uncertainty estimates. READ MORE