Sökning: "bagging"

Visar resultat 1 - 5 av 18 uppsatser innehållade ordet bagging.

  1. 1. Topological recursive fitting trees : A framework for interpretable regression extending decision trees

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

    Författare :Alexandre Tadros; [2020]
    Nyckelord :;

    Sammanfattning : Many real-world machine learning applications need interpretation of an algorithm output. The simplicity of some of the most fundamental machine learning algorithms for regression, such as linear regression or decision trees, facilitates interpretation. However, they fall short when facing complex (e.g. LÄS MER

  2. 2. Ensemble approach to code smell identification : Evaluating ensemble machine learning techniques to identify code smells within a software system

    Master-uppsats, Jönköping University/JTH, Datateknik och informatik

    Författare :Alfred Johansson; [2020]
    Nyckelord :Ensemble machine learning; code smell; technical debt; code smell identification; automated code smell identification;

    Sammanfattning : The need for automated methods for identifying refactoring items is prelevent in many software projects today. Symptoms of refactoring needs is the concept of code smells within a software system. Recent studies have used single model machine learning to combat this issue. LÄS MER

  3. 3. Enhance pilot's decision : Determination of balanced field length using neural network

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

    Författare :Antony Wan; [2020]
    Nyckelord :;

    Sammanfattning : The data reliability is crucial in aeronautics because the least miscalculation can lead to crash. Among these data, the balanced field length (BFL) is defined as the shortest field length at which both the take-off and the acceleration-stop can be performed. LÄS MER

  4. 4. Machine Learning for Predictive Maintenance on Wind Turbines : Using SCADA Data and the Apache Hadoop Ecosystem

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :John Eriksson; [2020]
    Nyckelord :Predictive maintenance; machine learning; hadoop; spark; mllib; apache; wind turbine; wind turbines; stacking; bagging; multilayer perceptron; decision tree; random forest;

    Sammanfattning : This thesis explores how to implement a predictive maintenance system for wind turbines in Apache Spark using SCADA data. How to balance and scale the data set is evaluated, together with the effects of applying the algorithms available in Spark mllib to the given problem. LÄS MER

  5. 5. An IoT Solution for Urban Noise Identification in Smart Cities : Noise Measurement and Classification

    Master-uppsats, Linnéuniversitetet/Institutionen för fysik och elektroteknik (IFE)

    Författare :Yasser Alsouda; [2019]
    Nyckelord :urban noise; sound pressure level SPL ; internet of things IoT ; machine learning; support vector machine SVM ; k-nearest neighbors KNN ; bootstrap aggregating Bagging ; random forest; mel-frequency cepstral coeffi-cients MFCC ;

    Sammanfattning : Noise is defined as any undesired sound. Urban noise and its effect on citizens area significant environmental problem, and the increasing level of noise has become a critical problem in some cities. Fortunately, noise pollution can be mitigated by better planning of urban areas or controlled by administrative regulations. LÄS MER