kNearest Neighbors (Batch Version)
This algorithm is a batch version of the kNearest Neighbors, Cosine Neighbor Similarity, single vertex. It makes a prediction for every vertex whose label is not known (i.e., the attribute for the known label is empty), based on its k nearest neighbors' labels.
Specifications
tg_knn_cosine_all(SET<STRING> v_type, SET<STRING> e_type, SET<STRING> re_type,
STRING weight, STRING label, INT top_k, BOOL print_accum = TRUE,
STRING file_path = "", STRING attr = "")
Time complexity
This algorithm has a complexity of \$O(E^2 / V)\$, where \$E\$ is the number of edges and \$V\$ is the number of vertices.
Characteristic  Value 

Result 
The predicted label for the vertices whose label attribute is empty. The result is available in three forms:

Input Parameters 

Result Size 
V = number of vertices 
Graph Types 
Undirected or directed edges, weighted edges 
Example
For the movie graph shown in the single vertex version, run knn_cosine_all, using topK=3. Then you get the following result:
{
"Source": [
{
"v_id": "Jing",
"v_type": "Person",
"attributes": {
"name": "Jing",
"known_label": "",
"predicted_label": "",
"@predicted_label": "a"
}
},
{
"v_id": "Neil",
"v_type": "Person",
"attributes": {
"name": "Neil",
"known_label": "",
"predicted_label": "",
"@predicted_label": "b"
}
},
{
"v_id": "Elena",
"v_type": "Person",
"attributes": {
"name": "Elena",
"known_label": "",
"predicted_label": "",
"@predicted_label": ""
}
}
]
}
]