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Subject: Apache Spark ×

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    ItemOpen Access
    Advisory system for adapting a single machine problem to a distributed solution
    (SDU University, 2024) Orynbekova Kamila
    General characteristics of the work. The work encompasses developing an advisory system to recommend solutions for single-machine problems adaptable to distributed systems, mainly focusing on implementation within the MapReduce platform. Methodologically, an experiment evaluated learning effectiveness, while extensive data collection informed model development. Predictive models, including Naive Bayes and Logistic Regression, were optimized and integrated into a recommendation system validated through rigorous evaluation. The aim of the research is to develop an advisory system that recommends single-machine problem solutions that adapt to distributed systems and are suitable for implementation on the MapReduce platform.
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    ItemOpen Access
    MBTI personality classification using Apache Spark
    (ResearchGate, 2021) Orynbekova K.; Talasbek A.; Omar A.
    Personality determines how person make decisions, speak or react on different situations. In this paper explained shortly the specifics of Myers-Briggs Type Indicator personality classification, then details of preparation of the experiment to run on Apache Spark platform. In experiment three different classification algorithms (Logistic Regression, Naive Bayes, Support Vector Machine) are used to train and predict MBTI personality pairs on a Kaggle dataset consisting of 8675 users tweets. In the end explained the data preprocessing and algorithm training, testing, validation details and results. The models with different vector combinations have been compared, and results have been described.