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finish of 6_1

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This commit is contained in:
Dominik Strzako 2021-05-15 15:04:56 +02:00
parent 03f103f437
commit 58887cac1e
2 changed files with 14 additions and 4 deletions
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8
Jenkinsfile_create_dataset
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@ -41,4 +41,12 @@ pipeline {
} }
} }
} }
post {
success {
build job: 's434788-training/master'
mail body: 'SUCCESS',
subject: 's434788 Creating dataset',
to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
}
} }

10
Zadanie_06_training.py
View File

@ -4,7 +4,8 @@ from sklearn.metrics import accuracy_score, classification_report
import pandas as pd import pandas as pd
from sklearn.model_selection import train_test_split from sklearn.model_selection import train_test_split
import numpy as np import numpy as np
import os import sys
wine=pd.read_csv('train.csv') wine=pd.read_csv('train.csv')
wine wine
@ -21,14 +22,15 @@ x_train, x_test, y_train, y_test = train_test_split(x,y , test_size=0.2,train_si
def regression_model(): def regression_model():
model = Sequential() model = Sequential()
model.add(Dense(16,activation = "relu", input_shape = (x_train.shape[1],))) model.add(Dense(4,activation = "relu", input_shape = (x_train.shape[1],)))
model.add(Dense(32,activation = "relu")) model.add(Dense(8,activation = "relu"))
model.add(Dense(8,activation = "relu"))
model.add(Dense(1,activation = "relu")) model.add(Dense(1,activation = "relu"))
model.compile(optimizer = "adam", loss = "mean_squared_error") model.compile(optimizer = "adam", loss = "mean_squared_error")
return model return model
model = regression_model() model = regression_model()
model.fit(x_train, y_train, epochs = 40, verbose = 1) model.fit(x_train, y_train, batch_size=int(sys.argv[1]), epochs = sys.argv[2]) #verbose = 1
model.save('wine_model') model.save('wine_model')