Delete temp.py

temp.py

-# -*- coding: utf-8 -*-
-"""
-Spyder Editor
-
-This is a temporary script file.
-"""
-
-#importing dataset
-
-import pandas as pd
-import matplotlib.pyplot as plt
-import numpy as np
-import seaborn as sn 
-
-dataset = pd.read_csv('DrDoS_NTP.csv') 
-
-#EDA
-
-dataset.head()
-dataset.columns
-dataset.head
-dataset.describe()
-
-#cleaning
-
-dataset.isna().any()
-
-
-#encoding 
-
-dataset = pd.get_dummies(dataset)
-dataset.columns
-dataset = dataset.drop(columns = [' Timestamp','Fwd PSH Flags',' Bwd PSH Flags',' Fwd URG Flags',' Bwd URG Flags'])
-
-
-#remove extra column
-
-attack_id = dataset['Flow ID']
-d_port = dataset[' Destination Port']
-state = dataset[' Inbound']
-dataset = dataset.drop(columns = ['Flow ID',' Destination Port',' Inbound'])
-
-#deviding into traing and testing
-
-from sklearn.model_selection import train_test_split
-X_train, X_test, y_train, y_test = train_test_split(dataset,state,test_size = 1, random_state = 0)
-
-
-# feture scaling
-from sklearn.preprocessing import StandardScaler
-sc_X = StandardScaler()
-X_train2 = pd.DataFrame(sc_X.fit_transform(X_train))
-X_test2 = pd.DataFrame(sc_X.transform(X_test))
-X_train2.columns = X_train.columns.values
-X_test2.columns = X_test.columns.values
-X_train2.index = X_train.index.values
-X_test2.index = X_test.index.values
-X_train = X_train2
-X_test = X_test2 
-
-## SVM (Linear)
-from sklearn.svm import SVC
-classifier = SVC(random_state = 0, kernel = 'linear')
-classifier.fit(X_train,y_train)
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