How to use gensim simple preprocess function

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by Abdul Rawoof A R dot icon Updated: Oct 9, 2023

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A preprocessing function is in the context of data science and machine learning. They must process or change it before machine learning or data analysis can use raw data. The primary purpose of a preprocessing function is to clean, format, and prepare the data.   

Here's a brief overview of these tasks and the libraries used for them:   

  • Linear Regression: It is a supervised ML technique. We use one or more input features to predict a continuous target variable. Scikit-Learn is a popular library for performing linear regression in Python. To make and train linear regression models, use the LinearRegression class in Scikit-Learn.   
  • Clustering: It is an unsupervised machine-learning technique. Users utilize it to group similar data points. Scikit-Learn provides various clustering algorithms like K-Means, DBSCAN, and Hierarchical Clustering.   
  • Dimensionality Reduction: These techniques reduce the number of features in a dataset. Principal Component Analysis (PCA) is a used method for dimensionality reduction.  


Here is an example of how to use gensim simple preprocess function:   

Fig: Preview the output you will get on running this code from your IDE.


In this solution, we are using the Gensim library.


Follow the steps carefully to get the output easily.

  1. Install PyCharm Community Edition on your computer.
  2. Open the terminal and install the required libraries with the following commands.
  3. Install Gensim - pip install gensim.
  4. Create a new Python file(e.g.:
  5. Copy the snippet using the 'copy' button and paste it into that file(remove output lines).
  6. Run the file using the run button.

I hope you found this useful. I have added the link to dependent libraries, and version information in the following sections.

I found this code snippet by searching for 'Correct way of using Phrases and preprocess_string gensim' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in PyCharm 2022.3.3.
  2. The solution is tested on Python 3.9.7.
  3. Gensim version 4.3.0.

Using this solution, we are able to use the gensim simple preprocess function with simple steps. This process also facilitates an easy-to-use, hassle-free method to create a hands-on working version of code which would help us to use the gensim simple preprocess function.

gensimby RaRe-Technologies

Python doticonstar image 14417 doticonVersion:4.3.0doticon
License: Weak Copyleft (LGPL-2.1)

Topic Modelling for Humans


            gensimby RaRe-Technologies

            Python doticon star image 14417 doticonVersion:4.3.0doticon License: Weak Copyleft (LGPL-2.1)

            Topic Modelling for Humans

                      Dependent Library

                      You can also search for any dependent libraries on kandi like 'Gensim'.


                      1. How can I use the gensim simple preprocess function for text data?   

                      Gensim's simple_preprocess function is a handy utility for preprocessing text data. Users tokenize and preprocess text documents. Here's how you can use it:   

                      • Import gensim   
                      • Use simple_preprocess to preprocess your text data. You can pass a single string or a list of strings as input.   

                      2. How does Natural Language Processing use the Gensim Simple Preprocess Function?   

                      NLP is a field of AI. It concentrates on the interaction between humans and computers through natural language. It encompasses various techniques and tools for processing and understanding human language. Gensim is a popular Python library for topic modeling and document similarity analysis. It includes a function called simple_preprocess that is often used in NLP pipelines.  


                      3. Can we use the Natural Language Toolkit for unsupervised topic modeling? Can we also use the Gensim Simple Preprocess Function?   

                      The Natural Language Toolkit (NLTK) and Gensim are separate Python libraries. You can use it together for unsupervised topic modeling. NLTK provides various text processing and preprocessing capabilities. To preprocess text data, combine Gensim's SimplePreprocess function and NLTK. 


                      4. Can I use a Word2Vec model with Gensim Simple Preprocess Function?   

                      You can use a Word2Vec model with the Gensim simple_preprocess function. However, it's crucial to know that we use simple methods to divide and prepare text data.  


                      5. What is the word tokenization? How does it help with the Gensim Simple Preprocess Function?   

                      Word tokenization is when you break down text into separate words or tokens. Tokens are words but can also be subwords, phrases, or other meaningful units. It depends on the specific tokenization method used. Tokenization is fundamental in natural language processing (NLP) and text analysis. It enables you to work with and analyze text data more granularly.  


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