Sökning: "AUPRC"

Hittade 3 uppsatser innehållade ordet AUPRC.

  1. 1. Exploring Alarm Data for Improved Return Prediction in Radios : A Study on Imbalanced Data Classification

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Matematiska institutionen

    Författare :Sofia Färenmark; [2023]
    Nyckelord :Imbalanced data classification; LASSO; Boruta; SVM; RFC; neural network; decision tree; AUC; AUPRC;

    Sammanfattning : The global tech company Ericsson has been tracking the return rate of their products for over 30 years, using it as a key performance indicator (KPI). These KPIs play a critical role in making sound business decisions, identifying areas for improvement, and planning. LÄS MER

  3. 2. Exploring DeepSEA CNN and DNABERT for Regulatory Feature Prediction of Non-coding DNA

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

    Författare :Jacob Stachowicz; [2021]
    Nyckelord :Machine Learning; Computer Science; Bioinformatics; Genomics; Transformer; Natural Language Processing; Whole Genome Sequencing; Non-codingDNA; DeepSEA; CNN; DNABert; BERT; DanQ; Biomedical Science; Computational Biology; AuROC; AUPRC; Maskininlärning; Datavetenskap; Bioinformatik; Genomik; Transformer; Språkteknologi; Helgenomsekvensering; icke-kod DNA; DeepSEA; CNN; DNABert; BERT; DanQ; Biomedicinsk vetenskap; Beräkningsbiologi; AuROC; AUPRC;

    Sammanfattning : Prediction and understanding of the regulatory effects of non-coding DNA is an extensive research area in genomics. Convolutional neural networks have been used with success in the past to predict regulatory features, making chromatin feature predictions based solely on non-coding DNA sequences. LÄS MER

  4. 3. Evaluation of machine learning methods for anomaly detection in combined heat and power plant

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

    Författare :Fredrik Carls; [2019]
    Nyckelord :Machine Learning; Anomaly detection; Fault detection; Health condition monitoring; Sensor surveillance; PHM; CHP Plant Boilers; k-Nearest Neighbor; One-Class Support Vector Machine; Auto-encoder; Maskininlärning; Anomalidetektion; Feldetektering; Tillståndsbevakning; Sensorövervakning; PHM; Kraftvärmeverkpannor; k-Nearest Neighbor; One-Class Support Vector Ma- chine; Auto-encoder;

    Sammanfattning : In the hope to increase the detection rate of faults in combined heat and power plant boilers thus lowering unplanned maintenance three machine learning models are constructed and evaluated. The algorithms; k-Nearest Neighbor, One-Class Support Vector Machine, and Auto-encoder have a proven track record in research for anomaly detection, but are relatively unexplored for industrial applications such as this one due to the difficulty in collecting non-artificial labeled data in the field. LÄS MER