How To Rock A categorical encoding That Will Save You Tons Of Time

How To Rock A categorical encoding That Will Save You Tons Of Time

The purpose of this article is comparison between categorical encoding strategies. This guide aims to assist you picking the right strategy based on your application.

A comparison between different categorical encoding strategies commonly used in the machine learning models preprocessing pipelines. This guide aims to assist you in selecting the right strategy based on your application.

Introduction

This post will discuss the different strategies to encode the categorical variables as a preprocessing step necessary to develop reliable machine learning models. Encode categorical variables is considered one of several actions that could enhance the model performance if applied appropriately. There are different encoding types; in this article, I picked the widely used encoders to discuss their pros and cons, and when it is appropriate to use as possible as I can. So, let’s get started.

Disclaimer: I attached an executable notebook for each encoding strategy hosted on kaggle. Each notebook has implementation in both pandas and sklearn, please feel free to run and report if you catch any bug or error.

In the end, I used sklearn to apply each strategy on the same dataset. After that, I utilized RandomForest and Logistic regression classifiers to compare each classifier’s performance based on the area under the curve — AUC.

machine-learning data-science pandas categorical-data data-preprocessing

What is Geek Coin

What is GeekCash, Geek Token

Best Visual Studio Code Themes of 2021

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

How To Build A Data Science Career In 2021

In Conversation With Dr Suman Sanyal, NIIT University,he shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.

Hire Machine Learning Engineer | Offshore Machine Learning Experts

We are a Machine Learning Services provider offering custom AI solutions, Machine Learning as a service & deep learning solutions. Hire Machine Learning experts & build AI Chatbots, Neural networks, etc. 16+ yrs & 2500+ clients.

The Difference between Data Science, Machine Learning and Big Data!

Many professionals and 'Data' enthusiasts often ask, “What's the difference between Data Science, Machine Learning and Big Data?”. Let's clear the air. If you are still wondering about it then this article is for you.

5 stages of learning Data Science

5 stages of learning Data Science and how to ace each of them

More Resources in AI, Data Science, and Machine Learning; Speeding up Scikit-Learn

More Resources for Women in AI, Data Science, and Machine Learning; Speeding up Scikit-Learn Model Training; Dask and Pandas: No Such Thing as Too Much Data; 9 Skills You Need to Become a Data Engineer; 8 Women in AI Who Are Striving to Humanize the World. It's a pity if you miss this great article.