13hannes11/UU_NCML_Project
1
0
Fork 0
mirror of https://github.com/13hannes11/UU_NCML_Project.git synced 2024-09-03 20:50:59 +02:00
Code Issues Projects Releases Wiki Activity

Grid size chosen such that node count=5*sqrt(N), closes #20

Browse Source
This commit is contained in:
Deepthi Pathare
2021-05-18 14:07:55 +02:00
parent 3dafda0ed7
commit d41a9b3a85
1 changed files with 4 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
german_analysis.py
View File

@@ -6,8 +6,9 @@ import voting_lib.voting_analysis as va
import numpy as np import numpy as np
# Training Paramters # Training Paramters
grid_h = 2 # Grid height # Grid size is chosen such that node count = 5*sqrt(N)
grid_w = 2 # Grid width grid_h = 11 # Grid height
grid_w = 11 # Grid width
radius = 2 # Neighbour radius radius = 2 # Neighbour radius
step = 0.5 step = 0.5
ep = 300 # No of epochs ep = 300 # No of epochs
@@ -15,7 +16,6 @@ ep = 300 # No of epochs
# Load data # Load data
dataset = ld.load_german_data() dataset = ld.load_german_data()
for period, df in dataset.items(): for period, df in dataset.items():
print("Election Period ", period) print("Election Period ", period)
@@ -27,5 +27,4 @@ for period, df in dataset.items():
model = va.train_model(X, grid_h, grid_w, radius, step, ep) model = va.train_model(X, grid_h, grid_w, radius, step, ep)
# Predict and visualize output # Predict and visualize output
va.predict(model, data, grid_h, grid_w) va.predict(model, data, grid_h, grid_w)