29 lines
720 B
Python
29 lines
720 B
Python
import statistics
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from funcClassifier import random_state_fit
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names = ['D1', 'TI1', 'V1', 'RH', 'P']
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def bring(data):
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return data[names], data['T'].astype('int')
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def worker():
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data = pd.read_csv('WindData.csv')
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x, y = bring(data)
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x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=100)
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funcs = ['relu', 'identity', 'tanh', 'logistic']
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acc = []
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for i in range(0, len(funcs)):
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acc.append(random_state_fit(i, x_train, y_train, x_test, y_test, funcs[i]))
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print('\n Results: ')
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print(f' Min is {min(acc)}, Median is {statistics.median(acc)}, Max is {max(acc)}')
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