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In machine learning, the kernel perceptron is a variant of the popular perceptron learning algorithm that can learn kernel machines, i.e. non-linear classifiers that employ a kernel function to compute the similarity of unseen samples to training samples. The algorithm was invented in 1964, making it the first kernel classification learner.
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Kernel perceptron | is a | variant of the popular perceptron learning algorithm that can learn kernel machines | 0.90 | text |
| Kernel perceptron | related to Variants and extensions | One | 0.60 | section |
| Kernel perceptron | related to Variants and extensions | Initially | 0.60 | section |
| Kernel perceptron | related to Variants and extensions | Moreover | 0.60 | section |
| Kernel perceptron | related to Variants and extensions | The | 0.60 | section |
| Kernel perceptron | related to Variants and extensions | It | 0.60 | section |
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