Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Database normalization is the cornerstone of database theory. Once a database is normalized, relationships between the data in multiple tables must be established. A hefty part of designing a ...

When the healthcare industry talks about data, the conversation usually focuses on interoperability and data standards. These are certainly important topics, but they don’t fully address the challenge ...

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

We collected a unique pair of microRNA sequencing data sets for the same set of tumor samples; one data set was collected with and the other without uniform handling and balanced design. The former ...

Comparison of expression data requires normalization. The optimum normalization method depends on sample type, with the most common being to normalize to reference genes. It is critical to select ...