Sökning: "model explainability"
Visar resultat 1 - 5 av 56 uppsatser innehållade orden model explainability.
1. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. LÄS MER
2. Unsupervised Online Anomaly Detection in Multivariate Time-Series
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/DatorteknikSammanfattning : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. LÄS MER
3. On modelling OMXS30 stocks - comparison between ARMA models and neural networks
Master-uppsats, Uppsala universitet/Matematiska institutionenSammanfattning : This thesis compares the results of the performance of the statistical Autoregressive integrated moving average (ARIMA) model and the neural network Long short-term model (LSTM) on a data set, which represents a market index. Both models are used to predict monthly, daily, and minute close prices of the OMX Stockholm 30 Index. LÄS MER
4. Increasing explainability of neural network based retail credit risk models
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Due to their ’black box’ nature, Artificial Neural Networks (ANN) are not permitted for use in various applications. One such application is mortgage credit risk modeling. LÄS MER
5. Explainable modeling in machine learning : A comparative study
Kandidat-uppsats, Umeå universitet/StatistikSammanfattning : As the use of advanced machine learning models has increased, the need for explainability that these models lack concerning their prediction has increased simultaneously. The aim of this thesis is to compare different functions available in the program R regarding their ability to provide explainability for these advanced machine learning models, also commonly referred to as black-box models. LÄS MER