Sökning: "Domain Analysis"
Visar resultat 1 - 5 av 989 uppsatser innehållade orden Domain Analysis.
1. Feature Selection for Microarray Data via Stochastic Approximation
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. LÄS MER
2. UNDER TVÅ MÅNAR En semantisk kartläggning av måne som ett kigo
Kandidat-uppsats, Göteborgs universitet/Institutionen för språk och litteraturerSammanfattning : This essay will examine the seasonal word known as kigo 季語 which mainly appears in the japanese haiku. The purpose is to offer a suggestion of how a systematic explanation of the semantic peculiarities of kigo could be conducted. The object of this semantic analysis is the kigo tsuki 月 (moon). LÄS MER
3. En kunskpaps översikt om bildämnets relevas i en förändelig tid.
Uppsats för yrkesexamina på grundnivå, Malmö universitet/Fakulteten för lärande och samhälle (LS)Sammanfattning : In response to the recent political decision in Sweden in 2023 to reduce the allocation of hours for visual art education in Swedish Schools Högstadiet (grade 7-9), this study is motivated by a commitment to substantiate our stance against this policy through scientific rationale. This paper undertakes a literature review to explore the significance of visual arts within the evolving landscape of educational curricula. LÄS MER
4. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. LÄS MER
5. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
Master-uppsats, Umeå universitet/Institutionen för tillämpad fysik och elektronikSammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. LÄS MER