Sökning: "High-dimensional data"

Visar resultat 11 - 15 av 114 avhandlingar innehållade orden High-dimensional data.

  1. 11. Network modeling and integrative analysis of high-dimensional genomic data : Nätverksmodellering och integrativ analys av högdimensionell genomikdata

    Författare :Jonatan Kallus; Göteborgs universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Mathmatical statistics; Biostatistics;

    Sammanfattning : Genomic data describe biological systems on the molecular level and are, due to the immense diversity of life, high-dimensional. Network modeling and integrative analysis are powerful methods to interpret genomic data. LÄS MER

  3. 12. Nearest Neighbor Classification in High Dimensions

    Författare :Sampath Deegalla; Henrik Boström; Slawomir Nowaczyk; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Nearest Neighbor; High-Dimensional Data; Curse of Dimensionality; Dimensionality Reduction; data- och systemvetenskap; Computer and Systems Sciences;

    Sammanfattning : The simple k nearest neighbor (kNN) method can be used to learn from high dimensional data such as images and microarrays without any modification to the original version of the algorithm. However, studies show that kNN's accuracy is often poor in high dimensions due to the curse of dimensionality; a large number of instances are required to maintain a given level of accuracy in high dimensions. LÄS MER

  4. 13. Valid causal inference in high-dimensional and complex settings

    Författare :Niloofar Moosavi; Xavier de Luna; Jenny Häggström; Edward Kennedy; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Causal inference; high dimension; sensitivity analysis; variable selection; convolutional neural network; semiparametric efficiency bound; Statistics; statistik;

    Sammanfattning : The objective of this thesis is to consider some challenges that arise when conducting causal inference based on observational data. High dimensionality can occur when it is necessary to adjust for many covariates, and flexible models must be used to meet convergence assumptions. The latter may require the use of a novel machine learning estimator. LÄS MER

  5. 14. Classification models for high-dimensional data with sparsity patterns

    Författare :Annika Tillander; Tatjana Pavlenko; Daniel Thorburn; Patrik Ryden; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; High-dimensionality; supervised classification; classification accuracy; sparse; block-diagonal covariance structure; graphical Lasso; separation strength; discretization; Statistics; statistik;

    Sammanfattning : Today's high-throughput data collection devices, e.g. spectrometers and gene chips, create information in abundance. However, this poses serious statistical challenges, as the number of features is usually much larger than the number of observed units. LÄS MER

  7. 15. Issues of incompleteness, outliers and asymptotics in high dimensional data

    Författare :Peter S. Karlsson; Thomas Holgersson; Ghazi Shukur; Åke E. Andersson; Jönköping University; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Business and economics; Ekonomi;

    Sammanfattning : This thesis consists of four individual essays and an introduction chapter. The essays are in the field of multivariate statistical analysis of High dimensional data. The first essay presents the issue of estimating the inverse covariance matrix alone and when it is used within the Mahalanobis distance in High-dimensional data. LÄS MER