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Corrected years
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@@ -17,9 +17,8 @@ ep = 300 # No of epochs
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# Load data
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dataset = ld.load_german_data()
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years = [2017, 2013, 2009]
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years = {17:2005, 18:2013, 19:2017}
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i = 0
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for period, df in dataset.items():
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print("Election Period ", period)
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@@ -31,6 +30,5 @@ for period, df in dataset.items():
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model = va.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, pc.get_compass_parties(year=years[i], country='de'))
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i += 1
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va.predict(model, data, grid_h, grid_w, pc.get_compass_parties(year=years[period], country='de'))
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