Sökning: "Data Partitioning"

Visar resultat 1 - 5 av 92 uppsatser innehållade orden Data Partitioning.

  1. 1. Unsupervised Clustering of Behavior Data From a Parking Application : A Heuristic and Deep Learning Approach

    Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

    Författare :Edvard Magnell; Joakim Nordling; [2023]
    Nyckelord :ML; Machine learning; clustering; unsupervised learning; deep learning; autoencoder; AI; artificial intelligence;

    Sammanfattning : This report aims to present a project in the field of unsupervised clustering on human behavior in a parking application. With increasing opportunities to collect and store data, the demands to utilize the data in meaningful ways also increase. LÄS MER

  3. 2. Scalable Nonparametric L1 Density Estimation via Sparse Subtree Partitioning

    Master-uppsats, Uppsala universitet/Statistik, AI och data science

    Författare :Axel Sandstedt; [2023]
    Nyckelord :density estimation; scalable density estimation; nonparametric density estimation; scalable nonparametric density estimation; L1; L_1; anomaly detection; regression analysis;

    Sammanfattning : We consider the construction of multivariate histogram estimators for any density f seeking to minimize its L1 distance to the true underlying density using arbitrarily large sample sizes. Theory for such estimators exist and the early stages of distributed implementations are available. LÄS MER

  4. 3. Evaluating clustering techniques in financial time series

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Johan Millberg; [2023]
    Nyckelord :clustering; machine learning; financial time series; time series; unsupervised learning; cluster validation; cluster evaluation; klustring; klusteranalys; finansiella tidsserier; maskininlärning; klustervalidering; evalueringsteknik;

    Sammanfattning : This degree project aims to investigate different evaluation strategies for clustering methodsused to cluster multivariate financial time series. Clustering is a type of data mining techniquewith the purpose of partitioning a data set based on similarity to data points in the same cluster,and dissimilarity to data points in other clusters. LÄS MER

  5. 4. A comparison of neuron touch detection algorithms utilising voxelization and the data structures octree, k-d tree and R-tree

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

    Författare :Jonathan Gustaf Cilli; Karin De Verdier; [2023]
    Nyckelord :;

    Sammanfattning : Simulations of biologically detailed neuronal networks have become an essential tool in the study of the brain. An important step in the creation of these types of simulations is the detection of the connections between the nerve cells. This paper analyses the efficiency of four algorithms used for such purposes. LÄS MER

  7. 5. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

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

    Författare :Ziyou Li; [2023]
    Nyckelord :Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Sammanfattning : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. LÄS MER