Sökning: "Interpretable Machine Learning"

Visar resultat 1 - 5 av 23 avhandlingar innehållade orden Interpretable Machine Learning.

  1. 1. Applied Machine Learning in Steel Process Engineering : Using Supervised Machine Learning Models to Predict the Electrical Energy Consumption of Electric Arc Furnaces

    Författare :Leo Carlsson; Pär Jönsson; Peter Samuelsson; Mikael Vejdemo-Johansson; Henrik Saxen; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Electric Arc Furnace; Electrical Energy Consumption; Statistical Modelling; Machine Learning; Interpretable Machine Learning; Predictive Modelling; Industry 4.0; Ljusbågsugn; Elenergiförbrukning; Statistisk Modellering; Maskininlärning; Tolkningsbar Maskininlärning; Prediktiv Modellering; Industri 4.0; Teknisk materialvetenskap; Materials Science and Engineering; Metallurgical process science; Metallurgisk processvetenskap;

    Sammanfattning : The steel industry is in constant need of improving its production processes. This is partly due to increasing competition and partly due to environmental concerns. One commonly used method for improving these processes is through the act of modeling. LÄS MER

  3. 2. Interpretable machine learning models for predicting with missing values

    Författare :Lena Stempfle; Chalmers tekniska högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; missing values; Machine learning; healthcare; interpretable machine learning;

    Sammanfattning : Machine learning models are often used in situations where model inputs are missing either during training or at the time of prediction. If missing values are not handled appropriately, they can lead to increased bias or to models that are not applicable in practice without imputing the values of the unobserved variables. LÄS MER

  4. 3. Patterns in big data bioinformatics : Understanding complex diseases with interpretable machine learning

    Författare :Mateusz Garbulowski; Jan Komorowski; Ryan J. Urbanowicz; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; complex diseases; big data; machine learning; transcriptomics; life sciences; rough sets; Bioinformatics; Bioinformatik;

    Sammanfattning : Alterations in the flow of genetic information may lead to complex diseases. Such changes are measured with various omics techniques that usually produce the so-called “big data”. Using interpretable machine learning (ML), we retrieved patterns from transcriptomics data sets. LÄS MER

  5. 4. Machine learning applications in healthcare

    Författare :Ana Luiza Dallora Moraes; Peter Anderberg; Johan Sanmartin Berglund; Martin Boldt; Arianit Kurti; Blekinge Tekniska Högskola; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Machine learning; Healthcare; Diagnosis; Prognosis; Age assessment; Bone age assessment; Dementia; Applied health technology; Tillämpad hälsoteknik; Applied Health Technology;

    Sammanfattning : Healthcare is an important and high cost sector that involves many decision-making tasks based on the analysis of data, from its primary activities up till management itself. A technology that can be useful in an environment as data-intensive as healthcare is machine learning. LÄS MER

  7. 5. Elucidation of complex diseases by machine learning

    Författare :Karolina Smolinska Garbulowska; Jan Komorowski; Claes Wadelius; Tuuli Lappalainen; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; machine learning; complex disease; multi-omics; regulatory element; gene regulation; transcription factor motif; networks; rough sets; Bioinformatics; Bioinformatik;

    Sammanfattning : Uncovering the interpretability of models for complex health-related problems is a crucial task that is often neglected in machine learning (ML). The amount of available data makes the problem even more complicated. LÄS MER