Sökning: "voting ensemble model"

Visar resultat 1 - 5 av 6 uppsatser innehållade orden voting ensemble model.

1. 1. Stock market analysis with a Markovian approach: Properties and prediction of OMXS30

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Max Aronsson; Anna Folkesson; [2023]
   Nyckelord :Markov chain; OMXS30; Markov chain properties; voting ensemble model; markovkedja; OMXS30; egenskaper hos markovkedjor; ensemble-modell;

   Sammanfattning : This paper investigates how Markov chain modelling can be applied to the Swedish stock index OMXS30. The investigation is two-fold. Firstly, a Markov chain is based on index data from recent years, where properties such as transition matrix, stationary distribution and hitting time are studied. LÄS MER

3. 2. Credit Card Approval Prediction : A comparative analysis between logistic regressionclassifier, random forest classifier, support vectorclassifier with ensemble bagging classifier.

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Dhanush Janapareddy; Narendra Chowdary Yenduri; [2023]
   Nyckelord :Machine Learning; Logistic Regression; Random Forest; Support Vector Machine; Ensemble Learning Bagging.;

   Sammanfattning : Background. Due to an increasing number of credit card defaulters, companies arenow taking greater precautions when approving credit applications. When a customermeets certain requirements, credit card firms typically use their experience todecide whether to grant them a credit card. LÄS MER

4. 3. Stronger Together? An Ensemble of CNNs for Deepfakes Detection

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Angelica Gardner; [2020]
   Nyckelord :deepfakes; deepfakes detection; supervised learning; binary classification; convolutional neural networks; ensemble learning; stacking;

   Sammanfattning : Deepfakes technology is a face swap technique that enables anyone to replace faces in a video, with highly realistic results. Despite its usefulness, if used maliciously, this technique can have a significant impact on society, for instance, through the spreading of fake news or cyberbullying. LÄS MER

5. 4. 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

7. 5. High-risk Consumer Credit Scoring using Machine Learning Classification

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Max Mjörnell; Ludvig Levay; [2019]
   Nyckelord :Machine learning; Scorecard modelling; Logistic regression; Support Vector Machine; Decision Tree; Random Forest; k-Nearest Neighbors; Artificial Neural Network; Voting ensemble; SHAP; LIME; Average Precision score; Feature engineering; Mathematics and Statistics;

   Sammanfattning : The use of statistical models in credit rating and application scorecard modelling is a thoroughly explored field within the financial sector and a central component in a credit institution’s underlying business model. The aim of this report was to apply and compare six different machine learning models in predicting credit defaults for high-risk consumer credits, using a data set provided by a Swedish consumer credit institute. LÄS MER