#!/usr/bin/env python
# coding: utf-8

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import pandas as pd
import numpy as np
df = pd.read_csv('/home/dearo/Desktop/DDOS/DataForDDOS.csv')


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feature_cols = ['Byte_Rate', 'Packet_Rate']
X = df[feature_cols]
y = df['Label']


# In[3]:


from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=5)


# In[4]:


from sklearn.neighbors import KNeighborsClassifier
k =5
my_knn = KNeighborsClassifier(n_neighbors = k)
my_knn.fit(X_train, y_train)
y_predict_knn = my_knn.predict(X_test)
accuracy = accuracy_score(y_test,y_predict_knn)


# In[9]:


d = [[1000,2000]]
df1 = pd.DataFrame(d,columns = feature_cols)
df1


# In[10]:


df2 = pd.read_csv(r'/home/dearo/OpenSatKit-master/cfs/build/exe/cfsat/ReadThisFile.csv')
np.savetxt(r'/home/dearo/OpenSatKit-master/cfs/build/exe/cfsat/WriteThisFile.txt', [my_knn.predict([df2.iloc[0]])],fmt='%s')


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