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# import libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression # Logistic regression

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# loading the dataset
df = pd.read_csv("diabetes.csv")
df.head()

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#Have the outcome data as y
y = df.Outcome.values

# remove the Outcome data from the dataset and have the remaining as x
x_data = df.drop(['Outcome'], axis=1)

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lr = LogisticRegression()
lr.fit(x_train, y_train)
print("test accuracy {}".format(lr.score(x_test, y_test)))

lr_score=lr.score(x_test, y_test)