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Now showing items 11-15 of 15
Comparative study of credit risk evaluation for unbalanced datasets using deep learning classifiers
(IEEE, 2023)
Credit risk assessment deals with calculating the risk of a loan not being repaid. For this reason, a lot of research effort is directed at credit risk analysis. In this study, machine learning models such as Light ...
Feature extraction for enhancing data-driven urban building energy models
(European Council on Computing in Construction (EC3), 2023)
Building energy demand assessment plays a crucial role in designing energy-efficient building stocks. However, most studies adopting a data-driven approach feel the deficiency of datasets with building-specific information ...
Incremental analysis of large-scale system logs for anomaly detection
(IEEE, 2019)
Anomalies during system execution can be detected by automated analysis of logs generated by the system. However, large scale systems can generate tens of millions of lines of logs within days. Centralized implementations ...
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)
Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ...
Evaluation of linguistic and prosodic features for detection of Alzheimer’s disease in Turkish conversational speech
(Springer Science+Business Media, 2015-12)
Automatic diagnosis and monitoring of Alzheimer’s disease can have a significant impact on society as well as the well-being of patients. The part of the brain cortex that processes language abilities is one of the earliest ...
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