A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

Learn how to use Python as a vector calculator for electric fields. This video shows how to represent charges and position vectors, compute field direction and magnitude, and solve problems faster ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Our study focused on using the Big Five personality inventory to predict traits from students' smartphone sensor data collected over 2 months under the Horizon Europe project. Through correlation ...

1 Department of Pediatrics, The First People’s Hospital of Nantong (Second Affiliated Hospital of Nantong University), Nantong, China 2 School of Nursing and Rehabilitation, Nantong University, ...

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

If you just want to test the emulator without installing a RISC-V compiler, you will find pre-built binaries in prebuilt/. The emulator provides a Python API that allows users to control execution, ...

Abstract: The Support Vector Machine (SVM) is a popular classification algorithm and is known for its generalization properties in machine learning. In this paper, we propose parallel implementation ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Ms. Mutcherson is a professor at Rutgers Law School. Right now in an Atlanta hospital room lies a 30-year-old nurse and mother, Adriana Smith. Ms. Smith, who is brain-dead, has been connected to life ...

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.