Merge branch 'Navindu' into 'master'

Navindu

See merge request !8

Slowloris Attack/slowlorisModel.py

@@ -31,7 +31,7 @@ from sklearn.metrics import classification_report
 import seaborn as sns
 
 # Importing the dataset
-dataset = pd.read_csv('/Users/harithachanuka/Documents/SLIIT/Research/Harry/Wanheda_Server/Slowloris/SlowlorisDATASET.numbers')
+dataset = pd.read_csv('SlowlorisDATASET.csv')
 
 # Read in data and display first 5 rows
 dataset.head()

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()
-