This repository contains the code that does exponential regression using gradient descent optimizer.
Consider the exponential regression, , after the log-transformation the equation becomes
.
Gradient Descent algorithm:
Step 1: Initialize the weights(loga & b) with random values and calculate Error (SSE)
Step 2: Calculate the gradient i.e. change in SSE when the weights (loga & b) are changed by a very small value from their original randomly initialized value. This helps us move the values of loga & b in the direction in which SSE is minimized.
Step 3: Adjust the weights with the gradients to reach the optimal values where SSE is minimized
Step 4: Use the new weights for prediction and to calculate the new SSE
Step 5: Repeat steps 2 and 3 till further adjustments to weights doesn’t significantly reduce the Error