Sökning: "general clustering procedure"

Hittade 4 uppsatser innehållade orden general clustering procedure.

  1. 1. Initialization of the k-means algorithm : A comparison of three methods

    Kandidat-uppsats, Stockholms universitet/Matematiska institutionen

    Författare :Simon Jorstedt; [2023]
    Nyckelord :k-means algorithm; clustering algorithm; Unsupervised Machine Learning;

    Sammanfattning : k-means is a simple and flexible clustering algorithm that has remained in common use for 50+ years. In this thesis, we discuss the algorithm in general, its advantages, weaknesses and how its ability to locate clusters can be enhanced with a suitable initialization method. LÄS MER

  3. 2. Machine Learning personalizationfor hypotension prediction

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Clara Escorihuela Altaba; [2022]
    Nyckelord :Arterial blood pressure; Hypotension prediction; Machine learning personal- ization; Domain adaptation; Data grouping; Arteriellt blodtryck; Börutsägelse av hypotoni; Personaliserad maskininlär- ning; Domänanpassning; Datagruppering.;

    Sammanfattning : Perioperative hypotension (PH), commonly a side effect of anesthesia,is one of the main mortality causes during the 30 posterior days of asurgical procedure. Novel research lines propose combining machinelearning algorithms with the Arterial Blood Pressure (ABP) waveform tonotify healthcare professionals about the onset of a hypotensive event withtime advance and prevent its occurrence. LÄS MER

  4. 3. Towards disease progression sub-typing via responsibility sampling for robust expectation-maximisation learning

    Master-uppsats, KTH/Optimeringslära och systemteori

    Författare :Mathias Edman; [2019]
    Nyckelord :;

    Sammanfattning : Most diseases have different heterogeneous effects on patients. Broadly, one may conclude what manifested symptoms correspond to which diagnosis, but usually there is more than one disease progression pattern. LÄS MER

  5. 4. Clusters (k) Identification without Triangle Inequality : A newly modelled theory

    Master-uppsats, Institutionen för informatik och media

    Författare :Naga Sambu Reddy Narreddy; Tuğrul Durgun; [2012]
    Nyckelord :K-means clustering; modifying K-means clustering; nearest neighbor clustering; general clustering procedure; Kolmogorov Simonov-test; parameters descriptions;

    Sammanfattning : Cluster analysis characterizes data that are similar enough and useful into meaningful groups (clusters).For example, cluster analysis can be applicable to find group of genes and proteins that are similar, to retrieve information from World Wide Web, and to identify locations that are prone to earthquakes. LÄS MER