Read on to learn more about what a t-test is, the different formulas used, and when to apply each type to compare means and ...

Learn what overfitting is, how it impacts data models, and effective strategies to prevent it, such as cross-validation and simplification.

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 ...

The University has completed its first ever Common Data Set (CDS) report, an annual survey jointly administered by the College Board, U.S. News and World Report, and Peterson’s and meant to ...

The train-validate-test process is hard to sum up in a few words, but trust me that you'll want to know how it's done to avoid the issue of model overfitting when making predictions on new data. The ...

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following explicit ...

Today's methods for BER (bit-error-rate) testing of high-speed serial links such as PCIe and SATA rely on predetermined patterns that don't represent real-world situations. These patterns use a ...