Essays about: "Gaussian Mixture Models"

Showing result 1 - 5 of 31 essays containing the words Gaussian Mixture Models.

  1. 1. Hierarchical Clustering of Time Series using Gaussian Mixture Models and Variational Autoencoders

    University essay from Lunds universitet/Matematisk statistik

    Author : Per Wilhelmsson; [2019]
    Keywords : Clustering; Deep Learning; Machine Learning; Time Series; Variational Autoencoders; Gaussian Mixture Models; Mathematics and Statistics;

    Abstract : This thesis proposes a hierarchical clustering algorithm for time series, comprised of a variational autoencoder to compress the series and a Gaussian mixture model to merge them into an appropriate cluster hierarchy. This approach is motivated by the autoencoders good results in dimensionality reduction tasks and by the likelihood framework given by the Gaussian mixture model. READ MORE

  2. 2. Load Identification from Aggregated Data using Generative Modeling

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Tanay Rastogi; [2019]
    Keywords : ;

    Abstract : In the view of an exponential increase in demand for energy, there is a need to come up with a sustainable energy consumption system in residential buildings. Several pieces of research show that this can be achieved by providing real-time energy consumption feedback of each appliance to its residents. READ MORE

  3. 3. Understanding usage of Volvo trucks

    University essay from Högskolan i Halmstad/Akademin för informationsteknologi; Högskolan i Halmstad/Akademin för informationsteknologi

    Author : Oskar Dahl; Fredrik Johansson; [2019]
    Keywords : Machine Learning; Clustering; Usage Behaviors; Association Rule Mining; Gaussian Mixture Models;

    Abstract : Trucks are designed, configured and marketed for various working environments. There lies a concern whether trucks are used as intended by the manufacturer, as usage may impact the longevity, efficiency and productivity of the trucks. READ MORE

  4. 4. Customer segmentation of retail chain customers using cluster analysis

    University essay from KTH/Matematisk statistik

    Author : Sebastian Bergström; [2019]
    Keywords : Cluster analysis; customer segmentation; tEIGEN; MCLUST; K-means; NMF; Silhouette; Davies-Bouldin; big spenders; statistics; applied mathematics; unsupervised learning; Klusteranalys; kundsegmentering; tEIGEN; MCLUST; K-means; NMF; Silhouette; Davies-Bouldin; storkonsumenter; statistik; tillämpad matematik;

    Abstract : In this thesis, cluster analysis was applied to data comprising of customer spending habits at a retail chain in order to perform customer segmentation. The method used was a two-step cluster procedure in which the first step consisted of feature engineering, a square root transformation of the data in order to handle big spenders in the data set and finally principal component analysis in order to reduce the dimensionality of the data set. READ MORE

  5. 5. Optimizing process parameters to increase the quality of the output in a separator : An application of Deep Kernel Learning in combination with the Basin-hopping optimizer

    University essay from Linköpings universitet/Statistik och maskininlärning

    Author : Eric Herwin; [2019]
    Keywords : Industrial process; Optimization; Gaussian Process; Deep Kernel Learning; Basin-hopping;

    Abstract : Achieving optimal efficiency of production in the industrial sector is a process that is continuously under development. In several industrial installations separators, produced by Alfa Laval, may be found, and therefore it is of interest to make these separators operate more efficiently. READ MORE