Sökning: "Classification problem"

Visar resultat 11 - 15 av 849 uppsatser innehållade orden Classification problem.

  1. 11. Combining Cell Painting, Gene Expression and Structure-Activity Data for Mechanism of Action Prediction

    Master-uppsats, Uppsala universitet/Nationellt resurscentrum för biologi och bioteknik

    Författare :Erik Everett Palm; [2023]
    Nyckelord :bioinformatics; deep learning; machine learning; joint model; tabular data; image data;

    Sammanfattning : The rapid progress in high-throughput omics methods and high-resolution morphological profiling, coupled with the significant advances in machine learning (ML) and deep learning (DL), has opened new avenues for tackling the notoriously difficult problem of predicting the Mechanism of Action (MoA) for a drug of clinical interest. Understanding a drug's MoA can enrich our knowledge of its biological activity, shed light on potential side effects, and serve as a predictor of clinical success. LÄS MER

  3. 12. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis

    Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Laura Galera Alfaro; [2023]
    Nyckelord :Explainable Artificial Intelligence; Learning To Rank; Local ModelAgnostic Interpretability; Ranking Generalized Additive Models;

    Sammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER

  4. 13. Few-Shot Learning for Quality Inspection

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Jesper Palmér; Ahmad Alsalehy; [2023]
    Nyckelord :Few-Shot Learning; AI; Transformers; ViT Deviation; Vision Transformers;

    Sammanfattning : The goal of this project is to find a suitable Few-Shot Learning (FSL) model that can be used in a fault detection system for use in an industrial setting. A dataset of Printed Circuit Board (PCB) images has been created to train different FSL models. LÄS MER

  5. 14. Exploring State-of-the-Art Machine Learning Methods for Quantifying Exercise-induced Muscle Fatigue

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Abboud Afram; Danial Sarab Fard Sabet; [2023]
    Nyckelord :EMG; SEMG; STFT; CWT; SVM; CNN; GAN; DCGAN; BCE; SGD; deep learning; machine learning; muscle fatigue; DCGAN; spectrogram; CNN models; transfers learning; data augmentation; feature extraction;

    Sammanfattning : Muscle fatigue is a severe problem for elite athletes, and this is due to the long resting times, which can vary. Various mechanisms can cause muscle fatigue which signifies that the specific muscle has reached its maximum force and cannot continue the task. LÄS MER

  7. 15. Mitigating Unintended Bias in Toxic Comment Detection using Entropy-based Attention Regularization

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Fabio Camerota; [2023]
    Nyckelord :XLNet; BERT; Toxic Comment Classification; Entropy-based Attention Regularization; XLNet; BERT; Toxisk Kommentar Klassificering; Entropibaserad uppmärksamhetsreglering;

    Sammanfattning : The proliferation of hate speech is a growing challenge for social media platforms, as toxic online comments can have dangerous consequences also in real life. There is a need for tools that can automatically and reliably detect hateful comments, and deep learning models have proven effective in solving this issue. LÄS MER