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