Description:
Build models and perform predictions using the ridge regression method.
Syntax:
ridge(X, Y, learning_rate, iterations) |
The function fits together matrix X and vector Y using the ridge regression method and returns model information that includes coefficient matrix and and intercept. The model information can act as parameter F in ridge(X’, F) to perform a fitting computation |
ridge(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 ridge(X, Y, learning_rate, iterations) |
Return value:
A matrix or a vector
Example:
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A |
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1 |
[[1.1,1.1],[1.4,1.5],[1.7,1.8],[1.7,1.7],[1.8,1.9],[1.8,1.8],[1.9,1.8],[2.0,2.1],[2.3,2.4],[2.4,2.5]] |
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2 |
[16.3,16.8,19.2,18,19.5,20.9,21.1,20.9,20.3,22] |
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3 |
=ridge(A1,A2,0.01,10000) |
Fit A1 and A2 together using ridge regression method and return coefficient matrix A3(1) and intercept A3(2) . |
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4 |
=ridge(A1,A3) |
Perform prediction on A1 using model A3; the result can be compared with actual values in A2. |