Modeling Pattern Set Mining Using Boolean Circuits

Aoga, John O. R.; Nijssen, Siegfried; Schaus, Pierre

doi:10.1007/978-3-030-30048-7_36

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…In order to examine how weather shocks affect a person's desire to migrate in the six economies that rely heavily on agriculture, such as Burkina Faso, Ivory Coast, Mali, Mauritania, Niger, and Senegal, this research presents a tree-based Machine Learning (ML) technique. Using the train-validation-test procedure, we run a number of tree-based algorithms to create reliable and noise-resistant methods (Aoga et al 2020). The research Harrison et al (2020) proposed a framework for predicting the migratory paths of these displaced people using well-established machinelearning techniques.…”

Section: Introductionmentioning

confidence: 99%

Leveraging a novel machine learning approach to forecast income and immigration dynamics

Saxena,

Asbe,

Vashishth

2023

Multidiscip. Sci. J.

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Migration is one of the most important topics to emerge in the history of humanity. It is essential to anticipate human migration as exactly as possible in a variety of circumstances, including urban planning, trade, epidemics, the global expansion of diseases, and pandemic preparation, in order to generate successful public policy. Estimating potential future earnings for an individual, a firm, or an entire industry may be accomplished via the use of income projections. These data might be put to use to identify potential areas for growth and investment, as well as to devise strategies for adjusting both the employment landscape and the economy as a whole. It is possible to anticipate immigration by applying machine learning (ML), a technique that is presently used in almost every facet of modern life. In this research work, we presented the ML-based swarm-optimized binary regression-based xgboost method (also known as SO-BRXGB). According to the results of the research, the SO-BRXGB algorithms were the ones that were the most successful in the applications. In conclusion, the machine learning models for human migration prediction that were applied in this study will offer a flexible framework for predicting human migration under a variety of situations.

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Section: Introductionmentioning

confidence: 99%

Leveraging a novel machine learning approach to forecast income and immigration dynamics

Saxena,

Asbe,

Vashishth

2023

Multidiscip. Sci. J.

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RL-Net: Interpretable Rule Learning with Neural Networks

Dierckx

Veroneze

Nijssen

2023

Lecture Notes in Computer Science

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A Data Mining Algorithm for Accessing Research Literature in Electronic Databases

Owan

2022

Innovative Technologies for Enhancing Knowledge Access in Academic Libraries

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Searching and retrieving relevant research materials from electronic databases are difficult for many students and early career researchers. Many researchers have abandoned beneficial research projects because they believe that related literature is unavailable to ground their work. This chapter serves as a guide to students, professionals, and internet users on how to pull information from electronic databases easily. The chapter begins by clarifying the concept of electronic databases, the evolution of electronic databases, and the processes involved in indexing scholarly works in an electronic database. The advantages and disadvantages associated with the use of electronic databases are also discussed. The chapter describes how electronic database search works, with insights into some poor practices. The concept of Boolean operators and how they can be used to easily mine desired contents from electronic databases are discussed. The knowledge and use of Boolean operators might become unavoidable in enabling researchers to locate relevant materials for their projects.

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Modeling Pattern Set Mining Using Boolean Circuits

Cited by 3 publications

References 17 publications

Leveraging a novel machine learning approach to forecast income and immigration dynamics

Leveraging a novel machine learning approach to forecast income and immigration dynamics

RL-Net: Interpretable Rule Learning with Neural Networks

A Data Mining Algorithm for Accessing Research Literature in Electronic Databases

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