The presence of outliers has serious adverse effects on the modeling and forecasting of functional data. Therefore, outlier detection, aiming at identifying abnormal functional curves from a dataset, ...

This paper analyzes the resampling technique of jackknifing and its capability of detecting outliers in data envelopment analysis. It is well recognized that measured efficiency is sensitive to ...

In my last few articles, I've looked at a number of ways machine learning can help make predictions. The basic idea is that you create a model using existing data and then ask that model to predict an ...

Enterprise CIOs are under increasing pressure from global regulators to rein in sustainability shortfalls due to partner problems. SAP’s pitch is that most enterprise partners are already using SAP, ...

Based on an August 2020 report by Interpol, more people have been spending time online since the start of the coronavirus pandemic, which has resulted in increased cybercrime. UK Finance also claimed ...

Data analytics deals with making observations with various data sets, and trying to make sense of the data. When dealing with very large data sets, automated tools must be used to find patterns and ...

Big data techniques for sorting through massive amounts of data to identify aberrations are beginning to find a home in semiconductor manufacturing, fueled by new requirements in safety-critical ...

With increasing focus on quality and reliability across all segments beyond just automotive, medical and mil-aero, it is more critical than ever for companies to leverage every byte of test data at ...