Created
July 20, 2022 06:55
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# Save Model Using joblib | |
import pandas | |
from sklearn import model_selection | |
from sklearn.linear_model import LogisticRegression | |
import joblib | |
url = "https://raw.githubusercontent.com/jbrownlee/Datasets/master/pima-indians-diabetes.data.csv" | |
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class'] | |
dataframe = pandas.read_csv(url, names=names) | |
array = dataframe.values | |
X = array[:,0:8] | |
Y = array[:,8] | |
test_size = 0.33 | |
seed = 7 | |
X_train, X_test, Y_train, Y_test = model_selection.train_test_split(X, Y, test_size=test_size, random_state=seed) | |
# Fit the model on training set | |
model = LogisticRegression() | |
model.fit(X_train, Y_train) | |
# save the model to disk | |
filename = 'finalized_model.sav' | |
joblib.dump(model, filename) | |
# some time later... | |
# load the model from disk | |
loaded_model = joblib.load(filename) | |
result = loaded_model.score(X_test, Y_test) | |
print(result) |
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