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Showing result 1 - 5 of 46 essays matching the above criteria.
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1. The Power of Credit Scoring: Evaluating Machine Learning and Traditional Models in Swedish Retail Banking
University essay from Göteborgs universitet/Graduate SchoolAbstract : In this paper, we investigate and compare different credit scoring models, with special attention paid to machine learning approaches outperforming traditional models. We explore a recently proposed method called the PLTR model, which is a combination of machine learning and traditional logistic regression. READ MORE
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2. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions
University essay from KTH/Matematik (Avd.)Abstract : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. READ MORE
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3. Empirical Asset Pricing via Machine Learning - Evidence from the Chinese stock market
University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomiAbstract : 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. READ MORE
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4. Prompt-learning and Zero-shot Text Classification with Domain-specific Textual Data
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : The rapid growth of textual data in the digital age presents unique challenges in domain-specific text classification, particularly the scarcity of labeled data for many applications, due to expensive cost of manual labeling work. In this thesis, we explore the applicability of prompt-learning method, which is well-known for being suitable in few-shot scenarios and much less data-consuming, as an emerging alternative to traditional fine-tuning methods, for domain-specific text classification in the context of customer-agent interactions in the retail sector. READ MORE
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5. Comparative Analysis of Machine Learning Algorithms for Biometric Iris Recognition Systems
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: Biometric identification plays a crucial role in various industries such as retail, and banking. Among the different biometric traits, iris patterns have become a reliable means of identification due to their unique features. In our thesis, we focus on evaluating and comparing different machine learning algorithms for irisrecognition. READ MORE
