Titlebook: Machine Learning and Data Analytics for Solving Business Problems; Methods, Application Bader Alyoubi,Chiheb-Eddine Ben Ncir,Anis Jarboui B

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Real-Time K-Prototypes for Incremental Attribute Learning Using Feature Selection,istently better performance and gains more coherent clustering results in less time consuming. Also, performing feature selection before modeling data, in incremental attribute learning context, eases the learning process and speeds it up.

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Predicting Salaries with Random-Forest Regression,ging, as many factors need to be considered, and large real datasets for learning are scarce. For this reason, research on salary predictions is comparably rare and limited. In this study, we investigate whether and how an advanced machine-learning approach, namely ensembles of random-forest regress

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Data-Driven Analysis of Microfinance and Social Loans Before and During the COVID-19 Pandemic Usingsponsoring microenterprises. This role has become more important, especially with the widespread of COVID-19 pandemic and its economic repercussions on individuals and microenterprises. We propose in this chapter a data-driven study on the repercussions of the COVID-19 pandemic on the beneficiaries’

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Identification of Credit Risks Using Cluster Analysis and Behavioural Scoring During the COVID-19 Pn requires the establishment of new policies and strategies to assess risk levels. However, good strategies can only be developed if banks are able to differentiate between viable, non-viable, and viable but distressed debtors at a granular level, grouping borrowers with similar characteristics and

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Improving Sales Prediction for Point-of-Sale Retail Using Machine Learning and Clustering,stores provide useful services for consumers. Data analytics can be applied to improve the performance of this type of retailing by better predicting product sales and optimizing product availability. Large physical retail chains sell a wide range of products in different store locations which makes

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Telecom Customer Segmentation Using Deep Embedded Clustering Algorithm,s. Most telecom companies use customer segmentation to increase customer satisfaction, which entails dividing targeted customers into different groups based on demographics or usage perspectives such as gender, age group, buying behaviour, usage pattern, special interests, and other characteristics

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Semantic Image Quality Assessment Using Conventional Neural Network for E-Commerce Catalogue Manageems that interest them. In retail websites, all the items included in the catalogue are displayed in a particular order and classified into different categories. This manual grouping and ordering take plenty of time. Furthermore, the evaluation of image quality plays a very important role in managin

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Contextual Recommender Systems in Business from Models to Experiments,ons matching users specific contexts. In this respect, Recommended Systems (RS) have been used in different domains to assist users decision making by providing item recommendations and thereby improving the quality. Context-Aware Recommender Systems (CARS) go further, taking contexts (e.g., time, l