Data Preprocessing Techniques Quiz

What is tokenization in data preprocessing?

• The process of reducing words to their root form

• The process of converting words into valid dictionary forms

• The process of splitting text into smaller units

• The process of removing stop words

What does lemmatization consider that stemming does not?

• The number of syllables in the word

• The frequency of the word in the text

• The length of the word

• The context and part of speech of the word

What are stop words?

• Words that carry significant meaning

• Words that are always stemmed

• Common words that can be removed from text/ Words that carry significant meaning

• Words that are always lemmatized

Which of the following is NOT a preprocessing technique mentioned?

• Lemmatization

• Stemming

• Tokenization

• Normalization

When does overfitting happen?

• Low bias and High Variance

• High bias and Low Variance

• Low bias and Low Variance

• High bias and High Variance

Which of the following statements about unsupervised learning is FALSE?

• It can identify patterns in the absence of labeled data

• It requires a predefined target output

• Clustering is a commonly used unsupervised learning method

• It is often used for dimensionality reduction

In TF-IDF, we down-weigh commonly occurring words across multiple documents?

• True

• False

What is the main characteristic of the Bag of Words model?

• It captures word order in a document

• It converts text into numerical vectors based on word frequency

• It assigns higher weights to rare words

• It only considers adjacent word pairs in the text