Forecasting, Data Mining and Machine Learning

Description

Original contributions addressing both theoretical aspects and practical applications in the areas of Forecasting, Data Mining and Machine Learning are solicited.
This topic will focus on, but will not be limited to,  methods and tools for analyzing, understanding and  explaining large sets of data, searching for relationships in the data, forecasting and prediction. 

Today increasing quantities of data are available to organizations and it is extremely important the ability of searching data in order to capture significant characteristics and extract meaningful patterns and strategic knowledge. A major challenge, and a great opportunity, is to effectively use all of this data to make valuable decisions. Machine Learning techniques provide useful tools for data classification and feature extraction and support for data forecasting. 

Possible contributions may address theoretical contributions in this topic, new tools from mathematical programming and operations research, and novel modeling approaches as well as results of applications of these techniques and models to specific real  problems.