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Results tagged with gradient-descent
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user 239267
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.
3
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Large Feature Values for Gradient Descent
Recently, I work on a linear regression model of my project. I have 200 samples, each of which has only one feature, to train my model. When I try to apply gradient descent algorithm I cannot reach o …
- 517
2
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answer
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Feature Scaling in Regression
I have a dataset in which each sample has only two features. I designed my own gradient descent algorithm, and applied it to my dataset. However, I could not obtain a result. Then, I printed the param …
- 517