logistic regression

Information system of feedback monitoring in social networks for the formation of recommendations for the purchase of goods

This paper describes an information system for monitoring and analyzing reviews on social networks to form recommendations for the purchase of goods. This system is designed to be used by customers to speed up and facilitate the search for the necessary products on e-commerce resources. Successful selection of a quality product according to the desired criteria is extremely important, as it saves search time and customer money. Analyzing comments on the network, the information system recommends the product if there is a preponderance of positive feedback on it.

Research into machine learning algorithms for the construction of mathematical models of multimodal data classification problems

Currently, machine learning algorithms (ML) are increasingly integrated into everyday life. There are many areas of modern life where classification methods are already used. Methods taking into account previous predictions and errors that are calculated as a result of data integration to obtain forecasts for obtaining the classification result are investigated. A general overview of classification methods is conducted. Experiments on machine learning algorithms for multimodal data are performed.

Logistic Regression as Instrument for Analyzing Influence of Remittances on Economic Growth

In the article, the influence of remittances on economics growth in Ukraine was researched. In order to conduct the research the logistics regression was applied. Volumes of consumption, export and import were included into the logistics model as variables, which contribute to calculation of GDP. By changing remittances, we identified their level, which will lead to GDP growth. Specifically, it was found out that economic growth would be achieved if remittances will increase by 2% ceteris paribus.

Algorithmic and software means of handwritten symbols recognition.

In this article is considered the algorithm of logistic regression and construction of the neural network for the recognition of handwritten symbols in the image. Examples of implementation of two approaches for solving the problem of numerical recognition are given. The efficiency of using a neural network, as the provision of the most reliable recognition results, is explored.