Method __init__

pattern/vector/__init__.py:2052–2059

k-nearest neighbor (kNN) is a simple supervised learning method for text classification. Documents are classified by a majority vote of nearest neighbors (cosine distance) in the training data.

(self, k=10, distance=COSINE, train=[], baseline=FREQUENCY)

class KNN(Classifier):
    
    def __init__(self, k=10, distance=COSINE, train=[], baseline=FREQUENCY):
        """ k-nearest neighbor (kNN) is a simple supervised learning method for text classification.
            Documents are classified by a majority vote of nearest neighbors (cosine distance)
            in the training data.
        """
        self.k = k               # Number of nearest neighbors to observe.
        self.distance = distance # COSINE, EUCLIDEAN, ...
        Classifier.__init__(self, train, baseline)
        
    def train(self, document, type=None):
        """ Trains the classifier with the given document of the given type (i.e., class).