The nature of statistical learning theory
The nature of statistical learning theory
A tutorial on support vector regression
Statistics and Computing
Data Mining Methods and Models
Data Mining Methods and Models
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Improved supply chain management based on hybrid demand forecasts
Applied Soft Computing
Predicting object-oriented software maintainability using multivariate adaptive regression splines
Journal of Systems and Software
A neural clustering and classification system for sales forecasting of new apparel items
Applied Soft Computing
Software reliability prediction by soft computing techniques
Journal of Systems and Software
Sales forecasting using extreme learning machine with applications in fashion retailing
Decision Support Systems
The forecasting model based on wavelet ν-support vector machine
Expert Systems with Applications: An International Journal
Mining the customer credit using hybrid support vector machine technique
Expert Systems with Applications: An International Journal
Financial time series forecasting using independent component analysis and support vector regression
Decision Support Systems
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
Computational Statistics & Data Analysis
Taiwanese 3G mobile phone demand forecasting by SVR with hybrid evolutionary algorithms
Expert Systems with Applications: An International Journal
Electric load forecasting based on locally weighted support vector regression
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Application of seasonal SVR with chaotic immune algorithm in traffic flow forecasting
Neural Computing and Applications
An overview of statistical learning theory
IEEE Transactions on Neural Networks
Support vector machine with adaptive parameters in financial time series forecasting
IEEE Transactions on Neural Networks
Fashion retailing forecasting based on extreme learning machine with adaptive metrics of inputs
Knowledge-Based Systems
Information Sciences: an International Journal
Hybrid intelligent systems for predicting software reliability
Applied Soft Computing
Demand forecasting of perishable farm products using support vector machine
International Journal of Systems Science
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Since computer products are highly replaceable and consumer demand often changes dramatically with the invention of new computer products, sales forecasting is therefore always crucial for computer product sales management. When constructing a sales forecasting model, discussing and understanding the important predictor variables can help focus on improving sales management efficacy. Aiming at to select appropriate predictor variable and construct effective forecasting model, this study combines variable selection method and support vector regression (SVR) to construct a hybrid sales forecasting model for computer products. In order to evaluate the feasibility and performance of the proposed approach, this study compiles the weekly sales data of five computer products including Notebook (NB), Liquid Crystal Display (LCD), Main Board (MB), Hard Disk (HD), and Display Card (DC) from a computer product retailer as the illustrative example. The experimental results indicate that the proposed hybrid sales forecasting scheme can not only provide a better forecasting result than the four competing models in terms of forecasting error, but also exhibit the capability of identifying important predictor variables. Furthermore, useful information can be provided by discussing the identified predictor variables for the five different computer products, thereby increasing sales management efficacy.