Classifying smoking urges via machine learning

Classifying smoking urges via machine learning

BACKGROUND AND OBJECTIVE Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit at...

Classifying Movement Articulation for Robotic Arms via Machine Learning

Articulation via target-oriented approaches have been commonly used in robotics. Movement of a robotic arm can involve targeting via a forward or inverse kinematics approach to reach the target. We attempted to transform the task of controlling the motor articulation to a machine learning approach. Towards this goal, we built an online robotic arm to extract articulation datasets and have used ...

Classifying E-Mails Via Support Vector Machine

For addressing the growing problem of junk E-mail on the Internet, this paper proposes an effective E-mail classifying technique. Our work handles E-mail messages as semi-structured documents consisting of a set of fields with predefined semantics and a number of variable length free-text contents. The main contributions of this paper include the following: First, we present a Support Vector Ma...

Classifying Galaxy Morphology using Machine Learning

The goal of this project is to classify galaxy morphologies. Generally, galaxy morphologies fall into one of two categories: "early types" (elliptical galaxies) and spiral galaxies, like the Milky Way. Additionally, a celestial object of interest may be categorized as neither, which usually corresponds to an image of a point source (e.g. a star) or to an artifact of the data. Although humans ar...

Classifying Legal Norms with Active Machine Learning