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# lasso()

Description:

An external libaray function that builds models and performs predictions using the Lasso regression method.

Syntax:

 lasso(X, Y, learning_rate, iterations) The function fits together matrix X and vector Y using the Lasso regression method and returns model information that includes coefficient matrix and intercept. The model information can act as parameter F in lasso(X’, F) to perform a fitting computation lasso(X’, F) The function fits together two matices that have same number of columns – that is, perform predicitions on another matrix X’ using model F, and returns a vector

Parameter:

 X A matrix Y A vector having the same number of rows as matrix X learning_rate Learning rate that is a decimal between 0 and 1; default value is 0.01 iterations Number of iterations; default is 1000 X’ A matrix that has same number of columns as matrix X F The return result of lasso(X, Y, learning_rate, iterations)

Return value:

A matrix or a vector

Example:

A

1

[[19,1],[25,1],[31,1],[38,1],[44,1]]

2

[19,32.3,49,73.3,97.8]

3

=lasso(A1,A2,0.001,10000) Fit A1 and A2 together using Lasso regression method and return coefficient matrix A3(1) and intercept A3(2)

4

=lasso(A1,A3) Perform prediction on A1 using model A3; the result can be compared with actual values in A2