logistic regression

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.