Introduction to Machine Learning

Choose Weight Tuning Rule

We need to update the weights in $\hat{V}$ so that it matches the examples.
One algorithm is the Least Mean Squares rule:
LMS Weight update rule:

Select a training example $b$ at random
Compute $error(b)$: \[error(b) = V_{train}(b) - \hat{V}(b)\]
For each board feature $f_{i}$, update weight $w_{i}$: \[w_{i} \leftarrow w_{i} + c \cdot f_{i} \cdot error(b) \] where, $c$ is some small constant, say 0.1, to moderate the rate of learning.
Goto 1

José M. Vidal .

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