Essays about: "Cost-sensitive learning"

Showing result 1 - 5 of 7 essays containing the words Cost-sensitive learning.

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

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

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

    Abstract : 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. READ MORE

  3. 2. Imbalanced Predictions

    University essay from Lunds universitet/Statistiska institutionen

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

    Abstract : 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. READ MORE

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

    University essay from Lunds universitet/Statistiska institutionen; Lunds universitet/Nationalekonomiska institutionen

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

    Abstract : 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. READ MORE

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

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

    Abstract : 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. READ MORE

  6. 5. Modelling rare events using non-parametric machine learning classifiers - Under what circumstances are support vector machines preferable to conventional parametric classifiers?

    University essay from Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Author : Lukas Ma; [2021-04-06]
    Keywords : ;

    Abstract : Rare event modelling is an important topic in quantitative social science research. However, despite the fact that traditional classifiers based upon general linear models (GLM) might lead to biased results, little attention in the social science community is devoted to methodological studies aimed at alleviating such bias, even fewer of them have considered the use of machine learning methods to tackle analytical problems imposed by rare events. READ MORE