I am obviously confused with terms, and different concepts behind it. Each websites gives different intuitions. With all intuitions my brain is full of confusion now. Please help me to address what is right.
- Neural Network = Multi Layer Perceptron
- Linear Network/Regression = Neural Network ( with No hidden layer) only input and output layer.
This Link proves linear regression without hidden layer.
Now the confusion is with respect to binary output and continuous value?
Can I claim below points are also called Linear Regression?
The neural network with binary output with one or more hidden layers.
Some site claims linear regression means the continuous value output. If I have an MLP with hidden layers, and its output is continuous value (ex: house price), then is it called linear regression?
Neural Network with linear activation functions ( doesn't matter binary output, continuous output value, hidden layer)
Hope you understood my confusion.