Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Aprende Stemming | Natural Language Handling
Identifying the Most Frequent Words in Text

book
Stemming

The Porter Stemming Algorithm is a highly-regarded and commonly utilized method in natural language processing for stemming. Stemming, a process that involves truncating words to their root or base form, is achieved by systematically stripping away suffixes.

Recognized for its efficiency in processing English text, the Porter Stemmer operates on a sequence of rule-based approaches to eliminate common suffixes from words. This ability to streamline words to their stems significantly reduces the dimensionality of text data.

Tarea

Swipe to start coding

  1. Import the PorterStemmer class for stemming from NLTK.
  2. Create an instance of the PorterStemmer.
  3. Apply stemming to each word in the previously filtered list.

Solución

# Import the PorterStemmer class from NLTK for stemming
from nltk.stem import PorterStemmer

# Create an instance of the PorterStemmer
stemmer = PorterStemmer()

# Apply stemming to each word in the filtered list
stemmed_words = [stemmer.stem(word) for word in filtered_list]

# Display the stemmed words
stemmed_words

Mark tasks as Completed
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 1. Capítulo 6

Pregunte a AI

expand
ChatGPT

Pregunte lo que quiera o pruebe una de las preguntas sugeridas para comenzar nuestra charla

some-alt