represent.py 文件源码

def __init__(self, league_df):

        stat_matrix = []
        for i in range(len(league_df)):
            stat = make_stat_vector(i, league_df)
            stat_matrix.append(stat)

        kmeans = KMeans(init='k-means++', n_clusters=5, n_init=10)
        kmeans.fit(stat_matrix)

        centroid_array = kmeans.cluster_centers_

        positions = kmeans.predict(stat_matrix)

        league_df['vector'] = pd.Series(stat_matrix, index = league_df.index)
        league_df['position'] = pd.Series(positions, index = league_df.index)



        self.df = league_df
        self.centroids = kmeans.cluster_centers_

        self.map = make_position_map(centroid_array)