Sökning: "Feature Importance"

Visar resultat 16 - 20 av 316 uppsatser innehållade orden Feature Importance.

1. 16. Designing Diverse Features to Reduce the Filter Bubble Effect on Social Media

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

   Författare :Ramya Kandula; [2023]
   Nyckelord :Filter bubbles; recommender systems; diversity; social media; filter bubblor; rekommenderande system; mångfald; sociala medier;

   Sammanfattning : The filter bubble effect has been an active area of research that has been explored in various contexts within social media. Research on recommender system designs within filter bubbles has received a lot of attention, mainly due to its impact on the phenomena. LÄS MER

3. 17. Evaluating the Effect of Meta-Labeling on Equity Market Neutral Strategy

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Niclas Wölner-Hanssen; [2023]
   Nyckelord :Meta-Labeling; Probabilistic Sharpe Ratio; Equity Market Neutral; Mathematics and Statistics;

   Sammanfattning : This thesis aims to construct an Equity Market Neutral (EMN) strategy framework to predict intraday excess returns of stocks within the S&P 500 index by utilizing machine learning techniques proposed by (López de Prado, 2018). The constructed EMN strategies within the framework utilizes techniques such as Stacked Single Feature Importance (SSFI), sample weighting, Probabilistic Sharpe Ratio (PSR), and meta-labeling. LÄS MER

4. 18. Prediction of dementia based on older adults’ sleep disturbances using machine learning: a controlled experiment.

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Joel Nyholm; [2023]
   Nyckelord :Dementia; Sleep; Risk factors; Machine learning;

   Sammanfattning : Background. Sleep disturbances can indicate an increased risk of dementia. This study examines whether machine learning can predict this association and which sleep disturbance factors impact dementia. Methods. LÄS MER

5. 19. Empirical Asset Pricing via Machine Learning - Evidence from the Chinese stock market

   D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

   Författare :Bao Liu; Chuyue Huan; [2023]
   Nyckelord :Machine learning; Asset pricing model; Chinese stock market;

   Sammanfattning : This thesis builds upon existing research on the application of machine learning in asset pricing in the US and European stock markets, by incorporating unique predictive indicators specific to the Chinese stock market, to explore whether machine learning can also be successfully applied in the Chinese stock market. Empirical results show that machine learning models outperform OLS significantly in predicting A-share returns, and this conclusion also applies to different portfolios we have constructed. LÄS MER

7. 20. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Humphry Takang Bate; [2023]
   Nyckelord :;

   Sammanfattning : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. LÄS MER