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https://github.com/13hannes11/UU_NCML_Project.git
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43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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#This code is modified to run in Kaggle
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#import voting_lib.load_data as ld
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#import voting_lib.voting_analysis as va
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import numpy as np
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import pandas as pd
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import os
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# Train model
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grid_h = 30 # Grid height
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grid_w = 30 # Grid width
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radius = 3 # Neighbour radius
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step = 0.5
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ep = 100 # No of epochs
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#main directory path(should contain differnt dataset directory) can be changed
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main_directory = '/kaggle/input'
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for dirname, _, filenames in os.walk(main_directory):
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#print(os.path.join(dirname))
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if dirname == main_directory: #to skip main directory path
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continue
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else:
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# Load data
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#data = ld.load_uk_data().to_numpy()
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#modifiy load_data.py --> load_uk_data() to load_uk_data(path)
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# --> Place path in directory -> for dirname, _, filenames in os.walk(path):
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data = load_uk_data(dirname).to_numpy()
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X = data[:,2:]
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#model = va.train_model(X, grid_h, grid_w, radius, step, ep)
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model = train_model(X, grid_h, grid_w, radius, step, ep)
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# Predict and visualize output
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#va.predict(model, data, grid_h, grid_w)
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predict(model, data, grid_h, grid_w) |