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برق و الکترونیک::
نمونه یادگیری
Each training example is called a training instance (or sample).
If we forced θ1 = 0, the algorithm would have only one degree of freedom and would have a much harder time fitting the data properly: all it could do is move the line up or down to get as close as possible to the training instances, so it would end up around the mean.
Moreover, some learn‐ ing algorithms are sensitive to the order of the training instances, and they perform poorly if they get many similar instances in a row.
This is in part because SGD deals with training instances independently, one at a time (which also makes SGD well suited for online learning), as we will see later.
Now we will look at very different ways to train a Linear Regression model, better suited for cases where there are a large number of features, or too many training instances to fit in memory.
واژگان شبکه مترجمین ایران