CODEWITHSUNDEEP
pythonmachine-learningscikit-learnlinear-regression
Arjun
Arjun

Reputation: 138

How to predict new output from a linearRegression model build using sklean?

I have been following tutorial on linear regression with scikitlearn.The code works perfectly and now i wanna predict new output by giving a new input.I have used student score and Study hour data set. Here's the code:

import  matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression

data=pd.read_csv("/home/crpsm/Pycharm/DataSet/student_scores.csv")

data.plot(x="Hours",y="Scores",style="o")
plt.title("Score-Hour")
plt.xlabel('Hours ')
plt.ylabel('Percentage ')


x=data.iloc[:,:-1]
y=data.iloc[:,1]

 x_train,x_test,y_train,y_test=train_test_split(x,y,train_size=0.55,random_state=5)

regression_model=LinearRegression()
regression_model.fit(x_train,y_train)

print(regression_model.coef_)
print(regression_model.intercept_)
regression_model.predict(X_test)

Upvotes: 0

Views: 166

Answers (1)

Joon-Ho Son
Joon-Ho Son

Reputation: 105

prediction = regression_model.predict(X)

Please read the docs: http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html

Upvotes: 1

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