text_plain_output_1.png
from sklearn.linear_model import LogisticRegression

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

data = pd.read_csv('../input/diabetes-dataset/diabetes.csv')
data

X = pd.DataFrame(data, columns=['Pregnancies', 'Glucose', 'BloodPressure', 'Skinthickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age'])
y = data.Outcome
X

model2 = LogisticRegression(solver='liblinear', C=10.0, random_state=0)
model2.fit(X, y)