Machine learning algorithms aren't just technological novelties relegated to tasks like picking out faces in crowded places. In the enterprise, they can surface patterns and relationships that would ...

Comparing die test results with other die on a wafer helps identify outliers, but combining that data with the exact location of an outlier offers a much deeper understanding of what can go wrong and ...

Outliers have the potential to skew analysis when they aren’t properly accounted for. Addressing outliers, specifically in trade cost analysis (TCA) data, is crucial for traders because it ensures the ...

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 ...

Development and Validation of a Machine Learning Approach Leveraging Real-World Clinical Narratives as a Predictor of Survival in Advanced Cancer Artificial intelligence (AI) models for medical image ...

After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft Research now uses a full code sample and step-by-step directions ...

Genome typing is the simultaneous genotyping of tens to hundreds of marker loci from across the genome in a single or few experiments (for example, by PCR amplification). The population-genomics ...