Sökning: "F1-score"
Visar resultat 1 - 5 av 308 uppsatser innehållade ordet F1-score.
1. Android Malware Detection Using Machine Learning
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background. The Android smartphone, with its wide range of uses and excellent performance, has attracted numerous users. Still, this domination of the Android platform also has motivated the attackers to develop malware. The traditional methodology which detects the malware based on the signature is unfit to discover unknown applications. LÄS MER
2. En undersökning av metoder förautomatiserad text ochparameterextraktion frånPDF-dokument med NaturalLanguage Processing
M1-uppsats, KTH/Hälsoinformatik och logistikSammanfattning : I dagens affärsmiljö strävar många organisationer efter att automatisera processen för att hämta information från fakturor. Målet är att göra hanteringen av stora mängder fakturor mer effektiv. Trots detta möter man utmaningar på grund av den varierande strukturen hos fakturor. LÄS MER
3. Leveraging CNN for Automated Peak Picking in Untargeted Metabolomics without Parameter Dependencies
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Metabolomics is a scientific discipline that involves the thorough analysis of small molecules, known as metabolites, found within a biological system. Furthermore, liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in metabolomics for analysing biological samples due to its broad coverage of the measurable metabolome. LÄS MER
4. Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks. LÄS MER
5. The influence of data annotation process requirements on performance criteria of ML models
Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : The data annotation process is a critical step in the development of machine learning (ML) models, as it entails labeling data to help supervised learning. This study investigates the impact of data annotation process requirements on the performance of ML models. LÄS MER