From f95ece73274da459a96ef75b42e889bbbf25d1b2 Mon Sep 17 00:00:00 2001
From: Purshottam <86057902+psrp7@users.noreply.github.com>
Date: Fri, 11 Nov 2022 09:43:13 +0530
Subject: [PATCH] Create linear reg

---
 ML/linear reg | 48 ++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 48 insertions(+)
 create mode 100644 ML/linear reg

diff --git a/ML/linear reg b/ML/linear reg
new file mode 100644
index 0000000..2f6d71b
--- /dev/null
+++ b/ML/linear reg	
@@ -0,0 +1,48 @@
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from sklearn import linear_model
+
+---------------------------------
+df=pd.read_csv("D:\\homeprices.csv")
+df
+--------------------------------
+%matplotlib inline
+plt.xlabel('area')
+plt.ylabel('price')
+plt.scatter(df.area,df.price,color='red',marker='+')
+----------------------------------------------------------
+
+reg=linear_model.LinearRegression()
+
+-----------------------------------------------
+reg.fit(df[['area']],df.price)
+
+------------------------------------
+reg.predict([[3300]])
+-----------------------------
+reg.coef_
+---------------------------------
+reg.intercept_
+-------------------------
+3300*135.78767123+180616.43835616432
+------------------------------------
+reg.predict([[5000]])
+---------------------------
+d=pd.read_csv("D:\\fp\\areas.csv")
+d
+------------------------------------------
+d.head(3)
+------------------
+reg.predict(d)
+----------------
+d['prices']=p
+--------------------
+d.to_csv("prediction.csv")
+----------------------------
+%matplotlib inline
+plt.xlabel('area')
+plt.ylabel('price')
+plt.scatter(df.area,df.price,color='red',marker='+')
+plt.plot(df.area,reg.predict(df[['area']]),color='blue')
+----------------------------------------------------------