Coefficients for linear regression model for dataset

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Reference no: EM132816656

In this problem, we write a program to find the coefficients for a linear regression model for the dataset provided (data2.txt). Assume a linear model: y = w0 + w1*x. You need to

1. Plot the data (i.e., x-axis for 1 st column, y-axis for 2 nd column), and use Python to implement the following methods to find the coefficients:

2. Normal equation, and

3. Gradient Descent using batch AND stochastic modes respectively:

a. Determine an appropriate termination condition (e.g., when cost function is less than a threshold, and/or after a given number of iterations).

b. Print the cost function vs. iterations for each mode; compare and discuss batch and stochastic modes in terms of the accuracy and the speed of convergence.

c. Choose a best learning rate. For example, you can plot cost function vs. learning rate to determine the best learning rate.

Reference no: EM132816656

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