LGApr 16, 2019
Forecasting Weakly Correlated Time Series in Tasks of Electronic Commerce
arXiv:1904.10927v120 citations
Originality Synthesis-oriented
AI Analysis
This work addresses forecasting challenges for e-commerce businesses, but it is incremental as it applies existing methods without introducing new techniques.
The paper tackled forecasting weakly correlated time series, specifically conversion rates for an e-commerce store, by comparing exponential smoothing, neural networks, and decision trees, finding that each method has distinct advantages and disadvantages.
Forecasting of weakly correlated time series of conversion rate by methods of exponential smoothing, neural network and decision tree on the example of conversion percent series for an electronic store is considered in the paper. The advantages and disadvantages of each method are considered.