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import splunk.Intersplunk 
import exec_anaconda
try:
    exec_anaconda.exec_anaconda()
except Exception as e:
    import cexc
    cexc.abort(e)
    sys.exit(1)

import sys

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import exec_anaconda
try:
    exec_anaconda.exec_anaconda()
except Exception as e:
    import cexc
    cexc.abort(e)
    sys.exit(1)

# Import this to get our "chunked" handler
from cexc import BaseChunkHandler

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requirements

WORK IN PROGRESS

1.) Python for Scientific Computing App

2.) Splunk ML Toolkit >=1.0

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demo@ip-10-0-0-200:/opt/splunk/bin$ ./splunk btool inputs list http --debug
/opt/splunk/etc/apps/splunk_httpinput/local/inputs.conf   [http]
/opt/splunk/etc/apps/splunk_httpinput/default/inputs.conf dedicatedIoThreads = 2
/opt/splunk/etc/apps/splunk_httpinput/local/inputs.conf   disabled = 0
/opt/splunk/etc/apps/splunk_httpinput/default/inputs.conf enableSSL = 1
host = splunk00
index = default
/opt/splunk/etc/apps/splunk_httpinput/default/inputs.conf maxSockets = 0
/opt/splunk/etc/apps/splunk_httpinput/default/inputs.conf maxThreads = 0
/opt/splunk/etc/apps/splunk_httpinput/default/inputs.conf port = 8088

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#!/usr/bin/env python

import sys

from sklearn.feature_extraction.text import CountVectorizer
from sklearn.decomposition import LatentDirichletAllocation

import pandas as pd
import numpy as np

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Customer Segmentation

This approach is taken directly from Chen, Sain, Guo (2012), and the data provided on the UCI Machine Learning Repository.

• Limit time to January 1st - December 1st.
• Add constaints to your search for United Kingdom, positive Quantity, positive UnitPrice, and a valid CustomerID

| search Country="United Kingdom" Quantity>0 UnitPrice>0 CustomerID=*

• Calculate a monetary field by multiplying Quantity and UnitPrice

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