[Solved] Why does this code raise an error? from sklearn.feature_extraction.... Why does this code raise an error? | NLP

NLP - Text Similarity and Search

Why does this code raise an error? from sklearn.feature_extraction.text import TfidfVectorizer texts = ['cat dog', 'dog mouse'] vectorizer = TfidfVectorizer() X = vectorizer.fit_transform(texts) sim = cosine_similarity(X[0], X[2]) print(sim)

AIndex 2 is out of range because only 2 documents exist

BTfidfVectorizer cannot process short texts

Ccosine_similarity requires dense arrays, not sparse

Dprint function is missing parentheses

Step-by-Step Solution

Solution:

Step 1: Check the number of documents
There are only 2 documents, indexed 0 and 1; index 2 is invalid.
Step 2: Understand error cause
Accessing X[2] causes an IndexError because it does not exist.
Final Answer:
Index 2 is out of range because only 2 documents exist -> Option A
Quick Check:
Index error due to invalid document index [OK]

Quick Trick: Check document count before indexing vectors [OK]

Common Mistakes:

MISTAKES

Assuming more documents than present
Blaming vectorizer for short texts
Ignoring zero-based indexing

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Why does this code raise an error?

Step 1: Check the number of documents

Step 2: Understand error cause

Final Answer:

Quick Check:

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