libcity.model.road_representation.DeepWalk

class libcity.model.road_representation.DeepWalk.DeepWalk(config, data_feature)

基类：libcity.model.abstract_traffic_tradition_model.AbstractTraditionModel

run(data=None)

参数

data – input of tradition model

返回

output of tradition model

class libcity.model.road_representation.DeepWalk.Graph

基类：collections.defaultdict

adjacency_iter()

check_self_loops()

degree(nodes=None)

has_edge(v1, v2)

make_consistent()

make_undirected()

nodes()

number_of_edges()

Returns the number of nodes in the graph

number_of_nodes()

Returns the number of nodes in the graph

order()

Returns the number of nodes in the graph

random_walk(path_length, alpha=0, rand=<random.Random object>, start=None)

Returns a truncated random walk. path_length: Length of the random walk. alpha: probability of restarts. start: the start node of the random walk.

remove_self_loops()

subgraph(nodes={})

libcity.model.road_representation.DeepWalk.build_deepwalk_corpus(G, num_paths, path_length, alpha=0, rand=<random.Random object>)

libcity.model.road_representation.DeepWalk.from_numpy(x, directed=False)

libcity.model.road_representation.DeepWalk.learn_embeddings(walks, dimensions, window_size, workers, iters, min_count=0, sg=1, hs=0)