Sökning: "SHAP"

Visar resultat 6 - 10 av 48 uppsatser innehållade ordet SHAP.

  1. 6. Can Machine Be a Good Stock Picker?: Bridging the Gap between Fundamental Data and Machine Learning

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

    Författare :Tomoya Narita; Povilas Stankevicius; [2023]
    Nyckelord :Machine Learning; XGBoost; Relative Valuation; Convergence Trade;

    Sammanfattning : We investigate the efficacy of historical accounting data and consensus forecasts for relative valuation of stocks, employing tree-based machine learning methods. We run an XGBoost model for monthly cross-sections of financial and pricing data of US equities from 1984 to 2021. LÄS MER

  3. 7. A Predictive Analysis of Customer Churn

    Kandidat-uppsats, KTH/Matematisk statistik

    Författare :Olivia Eskils; Anna Backman; [2023]
    Nyckelord :Churn prediction; CRM; optimization; applied mathematics; machine learning; gradient boosting; random forest; logistic regression; insurance industry; Kundbortfall; CRM; optimering; tillämpad matematik; maskininlärning; gradient boosting; random forest; logistisk regression; försäkringsbranschen;

    Sammanfattning : Churn refers to the discontinuation of a contract; consequently, customer churn occurs when existing customers stop being customers. Predicting customer churn is a challenging task in customer retention, but with the advancements made in the field of artificial intelligence and machine learning, the feasibility to predict customer churn has increased. LÄS MER

  4. 8. Counterfactual and Causal Analysis for AI-based Modulation and Coding Scheme Selection

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

    Författare :Kun Hao; [2023]
    Nyckelord :Explainable Artificial Intelligence; Counterfactual; Causal Analysis; Shapley Additive Explanations; Modulation and Coding Scheme; Förklarlig artificiell intelligens; kontrafaktisk analys; orsaksanalys; Shapley tillsatsförklaringar; modulerings och kodningsschema;

    Sammanfattning : Artificial Intelligence (AI) has emerged as a transformative force in wireless communications, driving innovation to address the complex challenges faced by communication systems. In this context, the optimization of limited radio resources plays a crucial role, and one important aspect is the Modulation and Coding Scheme (MCS) selection. LÄS MER

  5. 9. Unsupervised Anomaly Detection and Explainability for Ladok Logs

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Mimmi Edholm; [2023]
    Nyckelord :machine learing; anomaly detection; ml;

    Sammanfattning : Anomaly detection is the process of finding outliers in data. This report will explore the use of unsupervised machine learning for anomaly detection as well as the importance of explaining the decision making of the model. LÄS MER

  7. 10. Evolutionary Belief Rule based Explainable AI to Predict Air Pollution

    Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Sharif Noor Zisad; [2023]
    Nyckelord :Explainable AI; Explainability; Transparency; Belief Rule Based Expert System; Evolutionary Algorithm; Deep Learning;

    Sammanfattning : This thesis presents a novel approach to make Artificial Intelligence (AI) more explainable by using a Belief Rule Based Expert System (BRBES). A BRBES is a type of expert system that can handle both qualitative and quantitative information under uncertainty and incompleteness by using if-then rules with belief degrees. LÄS MER