Greg Rafferty raffg

## ip_address_regex.py
import re

text = ('0 13 127 196 245.0.0.1 255.255.255.255 this is text. '
        'Here is an incorrectly formatted ip address: 135.223.452.446 '
        'Here are some correct ones: 135.223.252.246, 0.0.0.1, 256.2.3.4, 14.46.34.65')

re.findall(r'\b(?:(?:1?[0-9]{1,2}|2[0-4][0-9]|25[0-5])\.){3}(?:1?[0-9]{1,2}|2[0-4][0-9]|25[0-5])\b', text)

# ['245.0.0.1', '255.255.255.255', '135.223.252.246', '0.0.0.1', '14.46.34.65']

## lda.csv

          
            Dominant_Topic
            Topic_Keywords
            Num_Documents
            Percent_Documents

            
              0.0
              harry, ron, malfoy, gryffindor, slytherin, wood, hermione, back, team, broom
              13
              0.0677

            
              1.0
              harry, snape, hermione, black, lupin, ron, back, sirius, door, eye
              17
              0.0885

            
              2.0
              harry, wand, light, back, hand, foot, face, feel, head, move
              24
              0.125

            
              3.0
              dumbledore, harry, sirius, fudge, ministry, wizard, kreacher, sit, order, office
              15
              0.0781

            
              4.0
              ron, harry, hermione, mrs_weasley, ginny, bill, back, yeah, -PRON-, room
              15
              0.0781

            
              5.0
              harry, malfoy, ron, slughorn, ginny, riddle, potion, sir, lockhart, good
              12
              0.0625

            
              6.0
              harry, uncle_vernon, dudley, back, dursley, aunt_petunia, owl, letter, room, house
              15
              0.0781

            
              7.0
              hagrid, harry, hermione, moody, yeh, back, ron, ter, -PRON-, cedric
              16
              0.0833

            
              8.0
              ron, harry, hermione, professor, umbridge, neville, table, back, class, year
              28
              0.1458

## sarimax.ipynb

      
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                raffg
                / sarimax.ipynb
            
            
              Created
              August 11, 2018 22:40
            
          
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## AirPassengers.ipynb

      
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                raffg
                / AirPassengers.ipynb
            
            
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              August 11, 2018 22:39
            
          
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## mse.py
SCRIPT_REAL(
'
import pandas as pd
import statsmodels.api as sm

dates = _arg1
passengers = _arg2
order_ar = min(_arg3)
order_i = min(_arg4)
order_ma = min(_arg5)

## forecast.py
SCRIPT_REAL(
'
import pandas as pd
import statsmodels.api as sm

dates = _arg1
passengers = _arg2
order_ar = min(_arg3)
order_i = min(_arg4)
order_ma = min(_arg5)

## results_table.md

      
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                raffg
                / results_table.md
            
            
              Last active
              February 18, 2018 04:25
            
          
Model
Accuracy
Precision
Recall
F1 Score


Gradient Boosting
95%
95%
95%
95%


Random Forest
94%
94%
95%
94%


AdaBoost
92%
92%
90%
91%


Logistic Regression
90%
90%
88%
89%


KNN
90%
91%
89%
90%


SVM
90%
90%
90%
90%


SVC
92%
92%
92%
92%


Multinomial Naive Bayes
84%
83%
82%
82%


## twitterbot.py
import tweepy
import json
from time import sleep

credentials = json.load(open('.env/twitter_credentials.json'))

consumer_key = credentials['consumer_key']
consumer_secret = credentials['consumer_secret']
access_token = credentials['access_token']
access_token_secret = credentials['access_token_secret']

## start_streaming.py
trumpstreamlistener = TrumpStreamListener()
start_stream()

## start_stream.py
def start_stream():
    while True:
        try:
            trumpstream = tweepy.Stream(auth, trumpstreamlistener)
            trumpstream.filter(follow=[realDonaldTrump])
        except:
            continue
	import re

	text = ('0 13 127 196 245.0.0.1 255.255.255.255 this is text. '
	'Here is an incorrectly formatted ip address: 135.223.452.446 '
	'Here are some correct ones: 135.223.252.246, 0.0.0.1, 256.2.3.4, 14.46.34.65')

	re.findall(r'\b(?:(?:1?[0-9]{1,2}\|2[0-4][0-9]\|25[0-5])\.){3}(?:1?[0-9]{1,2}\|2[0-4][0-9]\|25[0-5])\b', text)

	# ['245.0.0.1', '255.255.255.255', '135.223.252.246', '0.0.0.1', '14.46.34.65']
Dominant_Topic	Topic_Keywords	Num_Documents	Percent_Documents
0.0	harry, ron, malfoy, gryffindor, slytherin, wood, hermione, back, team, broom	13	0.0677
1.0	harry, snape, hermione, black, lupin, ron, back, sirius, door, eye	17	0.0885
2.0	harry, wand, light, back, hand, foot, face, feel, head, move	24	0.125
3.0	dumbledore, harry, sirius, fudge, ministry, wizard, kreacher, sit, order, office	15	0.0781
4.0	ron, harry, hermione, mrs_weasley, ginny, bill, back, yeah, -PRON-, room	15	0.0781
5.0	harry, malfoy, ron, slughorn, ginny, riddle, potion, sir, lockhart, good	12	0.0625
6.0	harry, uncle_vernon, dudley, back, dursley, aunt_petunia, owl, letter, room, house	15	0.0781
7.0	hagrid, harry, hermione, moody, yeh, back, ron, ter, -PRON-, cedric	16	0.0833
8.0	ron, harry, hermione, professor, umbridge, neville, table, back, class, year	28	0.1458
	SCRIPT_REAL(
	'
	import pandas as pd
	import statsmodels.api as sm

	dates = _arg1
	passengers = _arg2
	order_ar = min(_arg3)
	order_i = min(_arg4)
	order_ma = min(_arg5)
Model	Accuracy	Precision	Recall	F1 Score
Gradient Boosting	95%	95%	95%	95%
Random Forest	94%	94%	95%	94%
AdaBoost	92%	92%	90%	91%
Logistic Regression	90%	90%	88%	89%
KNN	90%	91%	89%	90%
SVM	90%	90%	90%	90%
SVC	92%	92%	92%	92%
Multinomial Naive Bayes	84%	83%	82%	82%
	import tweepy
	import json
	from time import sleep

	credentials = json.load(open('.env/twitter_credentials.json'))

	consumer_key = credentials['consumer_key']
	consumer_secret = credentials['consumer_secret']
	access_token = credentials['access_token']
	access_token_secret = credentials['access_token_secret']
	def start_stream():
	while True:
	try:
	trumpstream = tweepy.Stream(auth, trumpstreamlistener)
	trumpstream.filter(follow=[realDonaldTrump])
	except:
	continue