Add Linear Regression

Data Analytics/Linear Regression/LR.py

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+import pandas as pd
+from matplotlib import pyplot as plt
+
+def train(X,y):
+    mean_X = X.mean()
+    mean_y = y.mean()
+
+    numerator = 0
+    denominator = 0
+
+    for i in range(0,len(X)):
+        numerator += (X[i] - mean_X)*(y[i] - mean_y)
+        denominator += (X[i] - mean_X)**2
+
+    m = numerator/denominator
+    b = mean_y - (m*mean_X)
+
+    return m,b
+
+def plot(X,y,predicted):
+    plt.xlabel("Number of hours spent driving")
+    plt.ylabel("Risk Score")
+    plt.scatter(X,y)
+    plt.plot(X,predicted,color="green")
+    plt.savefig("Ass1.jpg")
+    plt.show()
+
+
+data = pd.read_csv("data.csv")
+X = data.iloc[:,0]
+y = data.iloc[:,1]
+
+m,b = train(X,y)
+predicted = []
+
+for i in range(0,len(X)):
+    temp = (m*X[i])+b
+    predicted.append(temp)
+    print(temp,y[i])
+

Data Analytics/Linear Regression/data.csv

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+X,Y
+8,3
+2,10
+11,3
+6,6
+5,8
+4,12
+12,1
+9,4
+6,9
+1,14