Merge pull request #88 from Aditi22Bansal/main

Adding Linear Regression Model- Solved issue #86

Linear Regression Model/Salary_dataset.csv

@@ -0,0 +1,31 @@
+,YearsExperience,Salary
+0,1.2000000000000002,39344.0
+1,1.4000000000000001,46206.0
+2,1.6,37732.0
+3,2.1,43526.0
+4,2.3000000000000003,39892.0
+5,3.0,56643.0
+6,3.1,60151.0
+7,3.3000000000000003,54446.0
+8,3.3000000000000003,64446.0
+9,3.8000000000000003,57190.0
+10,4.0,63219.0
+11,4.1,55795.0
+12,4.1,56958.0
+13,4.199999999999999,57082.0
+14,4.6,61112.0
+15,5.0,67939.0
+16,5.199999999999999,66030.0
+17,5.3999999999999995,83089.0
+18,6.0,81364.0
+19,6.1,93941.0
+20,6.8999999999999995,91739.0
+21,7.199999999999999,98274.0
+22,8.0,101303.0
+23,8.299999999999999,113813.0
+24,8.799999999999999,109432.0
+25,9.1,105583.0
+26,9.6,116970.0
+27,9.7,112636.0
+28,10.4,122392.0
+29,10.6,121873.0

Linear Regression Model/linear_regression.py

@@ -0,0 +1,41 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+from sklearn.linear_model import LinearRegression
+
+df=pd.read_csv("/kaggle/input/salary-dataset-simple-linear-regression/Salary_dataset.csv")
+
+plt.scatter(df['YearsExperience'],df['Salary'])
+plt.xlabel("X")
+plt.ylabel("Y")
+plt.title("Scatter Plot")
+plt.show()
+
+X=df[['YearsExperience']]
+y=df['Salary']
+
+model=LinearRegression()
+model.fit(X,y)  #calculates best fitting relation between x and y
+slope = model.coef_[0]  # represents coeff of x in y = mx + b
+intercept = model.intercept_  # point where regression lines crosses y axis
+
+def linear_regression(x):
+    return slope * x + intercept
+
+plt.scatter(df['YearsExperience'],df['Salary'], label='Data Points')
+plt.plot(df['YearsExperience'], [linear_regression(xi) for xi in df['YearsExperience']], color='red')
+plt.xlabel("X")
+plt.ylabel("Y")
+plt.legend()
+plt.title("Linear Regression")
+plt.show()
+
+new_x = 6
+prediction = linear_regression(new_x)
+print(f"Prediction for x = {new_x}: {prediction}")
+
+new_x = pd.DataFrame({"YearsExperience": [6]})
+print(model.predict(new_x))
+
+
+new_x = pd.DataFrame({'YearsExperience': [0]})
+print(model.predict(new_x))