code: def evaluate_embeddings(embeddings):
      X, Y = read_node_label("../data/wiki/wiki_labels.txt")
      tr_frac = 0.8
      print(
          "Training classifier using {:.2f}% nodes...".format(
              tr_frac * 100
          )
      )
      clf = Classifier(embeddings=embeddings, clf=LogisticRegression())
      clf.split_train_evaluate(X, Y, tr_frac)
  
file_path: GraphEmbedding/examples/sdne_wiki.py
imports: import numpy
  from ge.classify import read_node_label, Classifier
  from ge import SDNE
  from sklearn.linear_model import LogisticRegression
  import matplotlib.pyplot
  import networkx
  from sklearn.manifold import TSNE
label_desc: Use image node_id 1 for calling a global function with example usage: evaluate_embeddings(embeddings) without return types