openhgnn.models.HeCo¶
- class HeCo(meta_paths_dict, network_schema, category, hidden_size, feat_drop, attn_drop, sample_rate, tau, lam)[源代码]¶
Title: Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning
Authors: Xiao Wang, Nian Liu, Hui Han, Chuan Shi
HeCo was introduced in [paper] and parameters are defined as follows:
- 参数:
meta_paths (dict) – Extract metapaths from graph
network_schema (dict) – Directed edges from other types to target type
category (string) – The category of the nodes to be classificated
hidden_size (int) – Hidden units size
feat_drop (float) – Dropout rate for projected feature
attn_drop (float) – Dropout rate for attentions used in two view guided encoders
sample_rate (dict) – The nuber of neighbors of each type sampled for network schema view
tau (float) – Temperature parameter used for contrastive loss
lam (float) – Balance parameter for two contrastive losses