Advances, Systems and Applications
Table 2 Summary of different forecasting models
From: Efficient resource provisioning for elastic Cloud services based on machine learning techniques
Forecasting Model | Method | Parameters |
|---|---|---|
#1 | Last Value | Â |
#2 | Moving Average | MA(3) |
#3 | Linear Regression | AR(24) |
#4 | SVM - Polynomial Kernel | C=1.9, ε=0.027, p=1 |
#5 | SVM - Normal. Polyn. Kernel | C=1.9, ε=0.027, p=2 |
#6 | SVM - RBF Kernel | C=1.9, ε = 0.027, γ=0.2 |
#7 | SVM - RBF Kernel | C=1.9, ε = 0.027, γ=0.6 |
#8 | SVM - RBF Kernel | C=1.9, ε = 0.027, γ=1.0 |