Linear Regression_1.py

from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
model=LinearRegression()
y=y.reshape(-1,1) # reshaping the data
x=x.reshape(-1,1)
#spliting into test/train with a test size of .3 or 30 samples.
x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3,shuffle=True) 
model.fit(x_train,y_train) # fitting the model
print(model.score(x_test,y_test)) # get the r2 score
p=model.predict(x) # generate a prediction from the model using the original input
plt.plot(x,p,c='b',label='prediction')
plt.legend()