The Tasks of Analysis and Forecasting the Activities of IT Companies Using Machine Learning Methods 95
PhD in Physics and Matematics, Senior Lecturer, Moscow Aviation Institute (National Research University), Moscow, Russia
PhD in Physics and Matematics, Associate Professor, Moscow Aviation Institute (National Research University), Moscow, Russia
Student, Moscow Aviation Institute (National Research University), Moscow, Russia
The article describes applying machine learning methods for improving the efficiency of business processes when working with clients in an IT company. Two models of machine learning are considered: clustering the customer base and revenue forecasting.
The authors are grateful to G.F. Artamonov, General Director of OVIONT INFORM, for the data provided.
Dubes R.C., Jain A.K. Algorithms for Clustering Data.
Englewood Cliffs: Prentice Hall, 1988.
Shlens J. A tutorial on principal component analysis.
Institute for Nonlinear Science, UCSD, 2005.
Rui Xu, Wunsch D. Survey of clustering algorithms. IEEE
Transactions on Neural Networks, vol. 16, no. 3, 2005. pp. 645–678.
Wang L., Leckie C., Ramamohanarao K., Bezdek J.
Automatically Determining the Number of Clusters in Unlabeled Data Sets. IEEE
Transactions on Knowledge and Data Engineering, vol. 21, 2009. p.
Rousseeuw Peter J. Silhouettes: a Graphical Aid to the
Interpretation and Validation of Cluster Analysis. Computational and Applied
Mathematics, vol. 20, 1987. p. 53–65.
Lukashin Yu.P. Adaptivnye metody kratkosrochnogo
prognozirovaniya vremennyh ryadov. [Adaptive methods of short-term forecasting
of time series.] – M.: Finansy i statistika, 2003. (In Russ., Abstr. in