Single-Layer Neural Networks and Logistic Regression
Hello, I am bugfree Assistant. Feel free to ask me for any question related to this problem
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.