words.py
def most_similar(self, word: Text, n=10) -> List[Tuple[Text, int]]:
        """Finds the most similar words to a query word. Similarity is measured
        by cosine similarity (https://en.wikipedia.org/wiki/Cosine_similarity)
        over the word vectors.

        :param word: The query word.
        :param n: The number of most similar words to return.
        :return: The n most similar words to the query word.
        """
        #heapq.nlargest
        #scikit-learn
        word_vec = self.dic[word]
        cs_list = []
        for key, value in self.dic.items():
            cs = cosine_similarity(word_vec.reshape(1, -1), value.reshape(1, -1))
            cs_list.append((key, float(cs)))
        result = heapq.nlargest(n+1, cs_list, key = itemgetter(1))[1:]
        return result
Finds the most similar words to a query word. Similarity is measured
        by cosine similarity (https://en.wikipedia.org/wiki/Cosine_similarity)
        over the word vectors.

        :param word: The query word.
        :param n: The number of most similar words to return.
        :return: The n most similar words to the query word.
        
Finds the most similar words to a query word. Similarity is measured
by cosine similarity
over the word vectors.
Finds the most similar words to a query word . Similarity is measured by cosine similarity over the word vectors .
def most_similar(self, word: Text, n=10) -> List[Tuple[Text, int]]:
        word_vec = self.dic[word]
        cs_list = []
        for key, value in self.dic.items():
            cs = cosine_similarity(word_vec.reshape(1, -1), value.reshape(1, -1))
            cs_list.append((key, float(cs)))
        result = heapq.nlargest(n+1, cs_list, key = itemgetter(1))[1:]
        return result
def most_similar ( self , word : Text , n = 10 ) -> List [ Tuple [ Text , int ] ] : word_vec = self . dic [ word ] cs_list = [ ] for key , value in self . dic . items ( ) : cs = cosine_similarity ( word_vec . reshape ( 1 , - 1 ) , value . reshape ( 1 , - 1 ) ) cs_list . append ( ( key , float ( cs ) ) ) result = heapq . nlargest ( n + 1 , cs_list , key = itemgetter ( 1 ) ) [ 1 : ] return result
Finds the most similar words to a query word.
Finds the most similar words to a query word .
"""Finds the most similar words to a query word. Similarity is measured
        by cosine similarity (https://en.wikipedia.org/wiki/Cosine_similarity)
        over the word vectors.

        :param word: The query word.
        :param n: The number of most similar words to return.
        :return: The n most similar words to the query word.
        """ #heapq.nlargest #scikit-learn
The n most similar words to the query word.
The n most similar words to the query word .
self
word
Text
The query word.
The query word .
n
The number of most similar words to return.
The number of most similar words to return .