How to use IP address converted to integer in machine learning model

Question

I have a function to convert Ip address to integer value:

def convertIpToInt(ip):
    return sum([int(ipField) << 8*index for index, ipField in enumerate(reversed(ip.split('.')))])

convertIpToInt('149.170.10.1') -> 2510948865

which works fine and gives an integer value, but how to use these values in the classification model? Should I Scale these values, or what could be other options to handle this type of data?

normalization: datascience.stackexchange.com/questions/5885/… — sailfish009
– sailfish009, Commented Feb 27, 2020 at 4:43
almost everything has already solution: stackoverflow.com/questions/9810198/normalizing-ip-addresses — sailfish009
– sailfish009, Commented Feb 27, 2020 at 5:03
from ML perspective, converting ip addresses to numbers is a very bad idea. ip addresses are discrete and for any two ip addresses, ip1 > ip2 makes no sense. They can at best be represented as a set of discrete features but one hot encoding would give a very sparse representation, again overfitting the model. Try finding features that will help you represent ip addresses as discrete features without being sparse. for eg. Which country an ip belongs to from lite.ip2location.com/ip-address-ranges-by-country — dumbPy
– dumbPy, Commented Feb 27, 2020 at 13:13

Tushar Gupta · Accepted Answer · 2020-03-09 06:43:28Z

1

You have to convert IP into identifiers for your machine learning algorithm, for this you can use Label Encoders. This will convert your IP into numbers.

from sklearn import preprocessing le = preprocessing.LabelEncoder() le.fit(["ip1", "ip2", "ip3", "ip4"]) le.transform(["ip1", "ip2", "ip1"])

Link: https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html

If you think this can add weight to certain IP's(feature) then you can use One Hot encoding.

Link: https://machinelearningmastery.com/why-one-hot-encode-data-in-machine-learning/

edited Mar 9, 2020 at 6:43

answered Feb 27, 2020 at 12:43

Tushar Gupta

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