Sökning: "rating prediction"

Visar resultat 11 - 15 av 41 uppsatser innehållade orden rating prediction.

1. 11. Sound Quality Prediction Using Neural Networks

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :DEEPTI SHRIRAM KUNTE; [2020]
   Nyckelord :Sound quality; machine learning; neural networks; interpretation algorithms; Ljudkvalitet; maskininlärning; neuronnät; tolkningsalgoritmer;

   Sammanfattning : Sound quality is an important measure depicting the quality of a machine as well as the comfort in its usage. However, it being a subjective measure, not only is it difficult to capture it ahead of time but also necessitates time and cost expensive jury testing. LÄS MER

3. 12. Föreligger möjligheten att förutsäga miljöskandaler genom att analysera mätpunkter kopplade till ESG-data? : En kvantitativ studie

   Kandidat-uppsats, Högskolan i Gävle/Företagsekonomi

   Författare :Emir Smajic; Oskar Nordlander; [2020]
   Nyckelord :ESG; CSR; SRI; corporate scandal; environmental scandal; prediction; regression; ESG; CSR; SRI; företagsskandal; miljöskandal; prediktion; logistisk regression;

   Sammanfattning : Syfte: Företagsskandaler är ett högst relevant ämne då de ofta får stor medial uppmärksamhet och når investerare i snabb takt. En företagsskandal påverkar i många fall aktiepriset negativt samt får negativa finansiella konsekvenser för företagen. LÄS MER

4. 13. Comparison of supervised machine learning models forpredicting TV-ratings

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Sebastian Elf; Christopher Öqvist; [2020]
   Nyckelord :;

   Sammanfattning : Abstract Manual prediction of TV-ratings to use for program and advertisement placement can be costly if they are wrong, as well as time-consuming. This thesis evaluates different supervised machine learning models to see if the process of predicting TV-ratings can be automated with better accuracy than the manual process. LÄS MER

5. 14. Comparison and improvement of time aware collaborative filtering techniques : Recommender systems

   Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :David Grönberg; Otto Denesfay; [2019]
   Nyckelord :recommender systems; machine learning; collaborative filtering; movielens; Rekommendationssystem; maskininlärning;

   Sammanfattning : Recommender systems emerged in the mid '90s with the objective of helping users select items or products most suited for them. Whether it is Facebook recommending people you might know, Spotify recommending songs you might like or Youtube recommending videos you might want to watch, recommender systems can now be found in every corner of the internet. LÄS MER

7. 15. 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