IT17124904_Training Model

Slowloris.py

+# -*- coding: utf-8 -*-
+"""
+Created on Sat May 16 17:40:32 2020
+
+@author: navin
+"""
+
+
+# Simple Linear Regression
+
+# Importing the libraries
+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+
+# Importing the dataset
+dataset = pd.read_csv('dataset_7.csv')
+X = dataset.iloc[:, :-1].values
+y = dataset.iloc[:, 84].values
+
+# Splitting the dataset into the Training set and Test set
+from sklearn.model_selection import train_test_split
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 1/3, random_state = 0)
+
+# Training the Simple Linear Regression model on the Training set
+from sklearn.linear_model import LinearRegression
+regressor = LinearRegression()
+regressor.fit(X_train, y_train)
+
+# Predicting the Test set results
+y_pred = regressor.predict(X_test)
+
+# Visualising the Training set results
+plt.scatter(X_train, y_train, color = 'red')
+plt.plot(X_train, regressor.predict(X_train), color = 'blue')
+plt.title('Slowloris Attack Testing')
+plt.xlabel('X')
+plt.ylabel('Y')
+plt.show()
+
+# Visualising the Test set results
+plt.scatter(X_test, y_test, color = 'red')
+plt.plot(X_train, regressor.predict(X_train), color = 'blue')
+plt.title('Slowloris Attack Testing')
+plt.xlabel('X')
+plt.ylabel('Y')
+plt.show()
+