2 results
Search Results
Now showing 1 - 2 of 2
Item Open Access SEGMENTATION OF OUTLETS USING MACHINE LEARNING CLUSTERING AND CLASSIFICATION ALGORITHMS(СДУ хабаршысы - 2019, 2019) Nurmambetov D. ; Bogdanchikov A.Abstract. Segmentation of retail outlets in terms of manufacturing companies’ strategy applied in sales amount and trade activities for each of them is very important. Directed investments into outlets help companies to make more profit and decrease expenses. This study presents a method which can be used for outlets clustering using unsupervised and supervised machine learning algorithms comprising 2 steps – data partition using unsupervised Gaussian Mixture (GM) Model clustering algorithm based on outlets sales amount and further partition for one of them using Logistic Regression (LR) and Neural Networks (NN) classification algorithms, which predict whether outlets will achieve monthly sales plan. Previously, clustering was made without any special methods and clusters were formed using some agreed threshold values for outlets sales amount. The proposed algorithm was tested on real sales data and formed 3 clusters according to business needs. Sales plan achievement prediction gave up to 74% accuracy.Item Open Access TEACHING BIG DATA ANALYTICAL PLATFORMS IN HIGHER EDUCATION FOR GRADUATE DEGREE STUDENTS(СДУ хабаршысы - 2018, 2018) Nurkey U.T. ; Bogdanchikov A.Abstract. An extensive archive of petabytes of data has been generated from modern information systems and digital technologies such as scientific data analysis, social data analysis, reference systems and Internet services journals. To investigate and extract knowledge from this enormous data much effort is needed. Due to this, Big Data Management Systems need to be integrated as part of the computing curriculum. In this article, we present examples of analysed tasks that can be processed as large data projects using Apache Hadoop, and it’s Map – Reduce, Apache Spark, Hive and Pig by demonstrating how each type of system can be integrated via sample datasets and data analysis tasks. The aim of this paper is to show how Big data analyzing tools can be educated through sample tasks, their solution and implementation.