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Machine-Learning- Homework 3 Solved

Random Data Generator

a Univariate gaussian data generator

o Input 



Expectation value or mean: m 



Variance: s 



o Output: A data point trom N(m, s) 



0 HINT

You nave to handcraft your geneartor based on one ottne approaches given in the 



hyperlink. 



You can use uniform distribution function (Numpy) 



t). Polynomial basis linear model data generator 



W is an x 1 vector 



o Input: n (basis number), a, w 



wo:ro +
o Output: y (a number) 

o Internal constraint 

1.0 

1.0 

a: is uniformly distributed. 

Sequential Estimator 

Sequential estimate the mean and variance 

o Data is given trom the univariate qaussian data generator (1 *a). 

Input: (1 .a) Function: 

Call (1 to get a new data point trom N(m, s) 

o Use sequential estimation to find the current estimates to m and s

 

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