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Table 1
Overview of different classification and clustering algorithms with examples.
| Type | Classification | Clustering |
|
|
||
| Hard | nearest neighbour, | K-means, |
| Fisher’s linear | spectral clustering, | |
| discriminant analysis, | kernel PCA | |
| decision trees, support | ||
| vector machines | ||
|
|
||
| Soft | naïve Bayes, | Gaussian mixture |
| linear/quadratic | models | |
| discriminant analysis, | ||
| neural networks | ||
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