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- Title
K-Means Clustering Approach for Improving Financial Forecasts.
- Authors
Alexandru - Adrian, Ţole
- Abstract
The following paper treats both types of forecasting: qualitative and quantitative. It highlights the importance of using both of them in order to achieve more accurate forecasts. It shows the flaws of quantitative forecasting when applying simple regression on large sets of data. Also, by using advanced data analysis techniques, such as Big Data algorithms, the results of the quantitative forecasting can be drastically improved and it can be worthy of taking into consideration when drawing the conclusions. K-means algorithm it proves to be very effective when a quantitative forecast needs to be done. By using it we can successfully execute "drill-down forecasting" into specific activities.
- Subjects
ECONOMIC forecasting; DECISION making in business; QUANTITATIVE research; DATA mining; SCIENTIFIC method
- Publication
Ovidius University Annals, Series Economic Sciences, 2018, Vol 18, Issue 1, p514
- ISSN
2393-3127
- Publication type
Article