Skip to main content

Table 5 Dataset I and II along with steps parameters

From: A graphical heuristic for reduction and partitioning of large datasets for scalable supervised training

Parameter of

Parameter

Value

Dataset

Range of # data points

 

 Testing

3–600k

 Training

1–200k

 d

2

Step 1

# clustering iterations

5

Range of \(n_{c}\)

10–400

Step 2

nn

4

# ENS iterations

0

R

0.0–2.0

Step 3

GS edge cut

3.01

Step 4

# coarsening iterations

10

GC edge cut

3.10