A base class for Naive Bayes, k-NN and SVM. Trains a classifier on the given list of Documents or (document, type)-tuples, where document can be a Document, Vector, dict or string (dicts and strings are implicitly converted to vectors).
(self, train=[], baseline=FREQUENCY, **kwargs)
| 1664 | class Classifier(object): |
| 1665 | |
| 1666 | def __init__(self, train=[], baseline=FREQUENCY, **kwargs): |
| 1667 | """ A base class for Naive Bayes, k-NN and SVM. |
| 1668 | Trains a classifier on the given list of Documents or (document, type)-tuples, |
| 1669 | where document can be a Document, Vector, dict or string |
| 1670 | (dicts and strings are implicitly converted to vectors). |
| 1671 | """ |
| 1672 | self._vectors = [] # List of trained (type, vector)-tuples. |
| 1673 | self._classes = {} # Dict of (class, frequency)-items. |
| 1674 | self._baseline = baseline # Default predicted class. |
| 1675 | # Train on the list of Document objects or (document, type)-tuples: |
| 1676 | for d in (isinstance(d, Document) and (d, d.type) or d for d in train): |
| 1677 | self.train(*d) |
| 1678 | # In Pattern 2.5-, Classifier.test() is a classmethod. |
| 1679 | # In Pattern 2.6+, it is replaced with Classifier._test() once instantiated: |
| 1680 | self.test = self._test |
| 1681 | |
| 1682 | @property |
| 1683 | def features(self): |