In case the data is linearly separable, the optimal separating hyperplane is
What does it mean for your data to be linearly separable?
Thus, if the dataset is not linearly separable, this algorithm will not converge.
In the nonlinearly separable case, the above algorithms do not converge.
However, in practice, data are not often linearly separable.
The intersection of non-independent sets illustrates this.
Perceptrons can only solve linearly-separable problems.
Requêtes fréquentes français :1-200, -1k, -2k, -3k, -4k, -5k, -7k, -10k, -20k, -40k, -100k, -200k, -500k, -1000k,
Requêtes fréquentes anglais :1-200, -1k, -2k, -3k, -4k, -5k, -7k, -10k, -20k, -40k, -100k, -200k, -500k, -1000k,
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