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Instructions

Answer each of the following items. Be sure to follow the guidelines listed below under "Deliverable." Your work will be graded according a rubric.

What are the values of weights w$0,$ w$1,$ and w$2$ for the perceptron whose decision surface is illustrated in the figure? Assume the surface crosses the x$1$ axis at $-1$ and the x$2$ axis at $2.(30$ points$)$

Implement the perceptron learning algorithm $($PLA$)$ and linear regression $($pseudoinverse$)$ discussed in class. Please separate the problem in $3$ main steps, for each step indicate the command and describe what it executes.

Generation of the data and labeling. $(10$ points$)$

Apply and describe PLA. $(30$ points$)$

Apply and describe Linear regression by computing the pseudo inverse. $(30$ points$)$

Requirement:

You are required not to use the existing classifier and regression function in library.

Please submit your code in whatever language you prefer.

a$.$ Briefly discuss the sources of bias in supervised learning $(5$ points$)$

b$.$ Discuss the bias variance trade$-$off $(5$ points$)$