Single-Layer Neural Networks and Logistic Regression

Requirements Clarification & Assessment

• Understanding the Question: The question asks for a comparison between a single-layer neural network with one input and output and logistic regression, focusing on differences and similarities.
• Assumptions:
  • The neural network uses a sigmoid function as its activation function.
  • The term "single-layer" implies one hidden layer.
  • The neural network and logistic regression are both used for binary classification tasks.
• Objective: Identify key differences and similarities, ensuring a clear understanding of how each model functions and under what conditions they may be equivalent.
• Constraints:
  • Focus on theoretical and functional aspects rather than implementation details.
  • Consider the simplicity and complexity of each model.