The support vector machine has been a popular choice of classification method for many applications in machine learning. While it often outperforms other methods in terms of classification accuracy, the implicit nature of its solution renders the support vector machine less attractive in...

Traditional classifiers including support vector machines use only labeled data in training. However, labeled instances are often difficult, costly, or time consuming to obtain while unlabeled instances are relatively easy to collect. The goal of semi-supervised learning is to improve the...

This paper employs firm level benefit-cost and supply chain analyses to explore the reasons why a majority of Philippine seafood processing firms discontinued EU HACCP between 2004 and 2005. Results indicate that only 38% of firms remained certified, as they gained significantly from retention...

Costs necessary to conform with rules and regulations governing market access (i.e. compliance costs) are uncertain prior to export or collection of information which is not cost free for an individual firm. In this paper, we extend the heterogeneous firm model of Melitz to analyze how an...

This paper employs firm level benefit-cost and supply chain analyses to explore the reasons why a majority of Philippine seafood processing firms discontinued EU HACCP between 2004 and 2005. Results indicate that only 38% of firms remained certified, as they gained significantly from retention...

Agricultural decision makers rely on information provided by public and private entities. Data is a valuable asset and represents a tremendous investment of resources. However, difficulty locating sources and/or interpreting values may compromise its usefulness. The Florida citrus industry...