eli5 sklearn.feature_extraction.text.CountVectorizer This function uses the eli5 library to display the feature importance from a CountVectorizer. It first creates a pipeline with a CountVectorizer and eli5.show_weights, then fits the pipeline to the text data, retrieves the feature importance, and formats the output using a table formatter. Function 2024-12-07 16:29:06 29 views
eli5 sklearn.feature_extraction.text.CountVectorizer The code defines a function named random_eli5_function that randomly selects a function from the eli5 library to explain a given text. First, it randomly selects a function from the eli5 library, then randomly selects a text as input. Then, it creates a CountVectorizer object to convert the text into a feature matrix. Next, it uses the selected eli5 function to explain the model, and then formats the explanation using a table. Function 2024-12-07 16:16:20 5 views
Eli5 gensim This function uses the Eli5 library and the gensim library to calculate the frequency of words in a given text and displays the results using an Eli5 formatter. Function 2024-12-07 15:46:42 5 views
