Benefit transfer with limited data: An application to recreational fishing losses from surface mining

A Preliminary Economic Analysis of Recreational Fishing Losses Related to the Exxon Valdez Oil Spill

Enhancing Learning from Imbalanced Classes via Data Preprocessing: A Data-Driven Application in Metabolomics Data Mining

This paper presents a data mining application in metabolomics. It aims at building an enhanced machine learning classifier that can be used for diagnosing cachexia syndrome and identifying its involved biomarkers. To achieve this goal, a data-driven analysis is carried out using a public dataset consisting of 1H-NMR metabolite profile. This dataset suffers from the problem of imbalanced classes...

Efficient Data Mining with Evolutionary Algorithms for Cloud Computing Application

With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of ...

From data mining to knowledge mining: Application to intelligent agents

The last decade, the computers world became a huge wave of data. Data mining tasks were invoked to tackle this problem in order to extract the interesting knowledge. The recent emergence of some data mining techniques provide also many interesting induction rules. So, it is judicious now to process these induction rules in order to extract some new strong patterns called meta-rules. This work e...

Using Neural Networks with Limited Data to Estimate Manufacturing Cost

Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...