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Results tagged with gradient-descent
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user 418390
Gradient descent is a first-order iterative optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the gradient (or of the approximate gradient) of the function at the current point. For stochastic gradient descent there is also the [sgd] tag.
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ADALINE simple implementation with 2 features bug
I am reading Machine Learning with PyTorch and Ski-kit learn book by Sebastian Raschka
While plotting the decision boundary (a line in this case, since the number of features considered = 2) I can't f …
- 21
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votes
Accepted
ADALINE simple implementation with 2 features bug
The class boundary equation should be
$$
w1 * x1 + w2 * x2 + b = 0.5
$$
instead of
$$
w1 * x1 + w2 * x2 + b = 0
$$
since the threshold for prediction is 0.5
- 21