Sökning: "Linear discriminant analysis"

Visar resultat 1 - 5 av 24 uppsatser innehållade orden Linear discriminant analysis.

  1. 1. Mot robust cross-subject klassificering av electroencephalogram (EEG) baserad brain-computer interfacing (BCI):En genomförbarhetsstudie

    Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

    Författare :Shuai Wu; [2019]
    Nyckelord :;

    Sammanfattning : Brain-computer interface(BCI) är ett system där man kan skicka kommandon till dator med bara hjärnaktivitet. En sådan system är viktigt för människor lider av flera motorisk funktionshinder, då maskinen skulle kunna förbättra patienters liv genom att uppfylla deras behov. LÄS MER

  2. 2. Visualization and Classification of Neurological Status with Tensor Decomposition and Machine Learning

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Thi Pham; [2019]
    Nyckelord :Stress assessment; physiological signals; biosensors; tensor decomposition; feature visualization; machine learning;

    Sammanfattning : Recognition of physical and mental responses to stress is important for stress assessment and management as its negative effects in health can be prevented or reduced. Wearable technology, mainly using electroencephalogram (EEG), provides information such as tracking fitness activity, disease detection, and monitoring neurologicalstates of individuals. LÄS MER

  3. 3. Risk Free Credit: Estimating Risk of Debt Delinquency on Credit Cards : Using Machine Learning Methodology

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

    Författare :Andreas Magnedal Holmgren; Victor Sellstedt; [2019]
    Nyckelord :;

    Sammanfattning : A well functioning economy requires a stable credit market. Computational intelligence methods could provide a method to reduce the amount of uncertainty in the markets. This report examines four different methods for predicting the probability for defaults of credit card clients in Taiwan. LÄS MER

  4. 4. Evaluation of the Robustness of Different Classifiers under Low- and High-Dimensional Settings

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Linnea Lantz; [2019]
    Nyckelord :LDA; QDA; DLDA; DQDA; GQDA;

    Sammanfattning : This thesis compares the performance and robustness of five different varities of discriminant analysis, namely linear (LDA), quadratic (QDA), generalized quadratic (GQDA), diagonal linear (DLDA) and diagonal quadratic (DQDA) discriminant analysis, under elliptical distributions and small sample sizes.  By means of simulations, the performance of the classifiers are compared against separation of mean vectors, sample size, number of variables, degree of non-normality and covariance structures. LÄS MER

  5. 5. Evaluation of a Radiomics Model for Classification of Lung Nodules

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Parastu Rahgozar; [2019]
    Nyckelord :Lung Nodule; Radiomics; Tumor Classification;

    Sammanfattning : Lung cancer has been a major cause of death among types of cancers in the world. In the early stages, lung nodules can be detected by the aid of imaging modalities such as Computed Tomography (CT). In this stage, radiologists look for irregular rounded-shaped nodules in the lung which are normally less than 3 centimeters in diameter. LÄS MER