What role does the hinge loss function play in the context of binary classification using TensorFlow Quantum?
Tuesday, 11 June 2024 by EITCA Academy
The hinge loss function plays a pivotal role in the context of binary classification using TensorFlow Quantum (TFQ), a framework that integrates quantum computing with machine learning through TensorFlow. This loss function is particularly significant in the realm of support vector machines (SVMs) and can be adapted to quantum machine learning models to enhance their
How do we find the values of vector W and B in SVM?
Monday, 07 August 2023 by EITCA Academy
Support Vector Machines (SVM) is a powerful machine learning algorithm used for classification and regression tasks. In SVM, the goal is to find a hyperplane that maximally separates the data points of different classes. The values of the weight vector (W) and the bias term (B) in SVM are important in determining the position and
- Published in Artificial Intelligence, EITC/AI/MLP Machine Learning with Python, Support vector machine, Support vector assertion, Examination review
Tagged under: Artificial Intelligence, Classification, Hinge Loss, Optimization, Support Vector Machines, SVM