Sökning: "Cost-sensitive"

Visar resultat 1 - 5 av 15 uppsatser innehållade ordet Cost-sensitive.

  1. 1. Neural Networks for Predictive Maintenance on Highly Imbalanced Industrial Data

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

    Författare :Oscar Montilla Tabares; [2023]
    Nyckelord :Class Imbalance; Cost Sensitivity; Cost-Sensitive Learning; Focal Loss; Binary Classification; Machine Learning; Deep Learning;

    Sammanfattning : Preventive maintenance plays a vital role in optimizing industrial operations. However, detecting equipment needing such maintenance using available data can be particularly challenging due to the class imbalance prevalent in real-world applications. LÄS MER

  3. 2. Imbalanced Predictions

    Magister-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Stella Säfström; [2022]
    Nyckelord :Imbalanced data; cost-sensitive learning; SMOTE; random undersampling; Mathematics and Statistics;

    Sammanfattning : The aim of the thesis is to evaluate solutions to the class imbalance problem using real world data sets with varying degrees of class imbalance. The analysis is limited to binary classification. Three large data sets relating to credit card fraud, vehicle insurance and heart disease are used for the analysis. LÄS MER

  4. 3. Climate change mitigation policies and personal cost: Are young people more willing to bear the cost for a greener tomorrow?

    Master-uppsats, Lunds universitet/Statsvetenskapliga institutionen

    Författare :Sofia Henriks; [2022]
    Nyckelord :Climate change mitigation policies; Low-cost hypothesis theory; Experimental vignette survey; Climate generation gap; Cost-sensitivity; Law and Political Science;

    Sammanfattning : Even as the public awareness and concern about climate change are increasing, and the younger generations are urging for political action, support for more costly and ambitious mitigation policies is not given. The low-cost hypothesis theory provides an explanation for why our concern about climate change fails to translate into supporting policies when the personal cost is high. LÄS MER

  5. 4. Classification of Premium and Non-Premium Products using XGBoost and Logistic Regression

    Magister-uppsats, Lunds universitet/Statistiska institutionen; Lunds universitet/Nationalekonomiska institutionen

    Författare :Francisco Erazo; Stephany Rojas Gerena; [2022]
    Nyckelord :XGBoost; Logistic Regression; Classification Algorithms; Food and Beverage; Cost-Sensitive Analysis; SMOTE; Business and Economics;

    Sammanfattning : In the past few years, many industries have become interested in premium product segmentation to achieve higher unit margins. In this paper, we applied machine learning algorithms to predict whether a product is premium or non-premium. LÄS MER

  7. 5. Neonatal Sepsis Detection With Random Forest Classification for Heavily Imbalanced Data

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

    Författare :Ayman Osman Abubaker; [2022]
    Nyckelord :Random Forest; Neonatal Sepsis; Imbalanced Classification; Cost-sensitive; SMOTE; ADASYN; CNN; Tomek- Links;

    Sammanfattning : Neonatal sepsis is associated with most cases ofmortality in the neonatal intensive care unit. Major challengesin detecting sepsis using suitable biomarkers has lead people tolook for alternative approaches in the form of Machine Learningtechniques. LÄS MER