MLS-C01 Exploratory Data Analysis Practice Question
A machine learning engineer is analyzing a text classification dataset with 50,000 documents. Which EDA step is most important to understand the vocabulary size and frequency distribution?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Plot frequency of each word in a bar chart
Plotting the frequency of each word in a bar chart directly shows the vocabulary size and the frequency distribution (e.g., Zipfian distribution). This EDA step helps decide vocabulary cutoff by identifying very rare words that can be removed. Option A is wrong because TF-IDF is a feature transformation, not an exploratory step. Option C is wrong because bigram collocations are for detecting phrases, not for basic word frequency. Option D is wrong because document length distribution pertains to the number of words per document, not vocabulary size or word frequency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Compute TF-IDF matrix
Why it's wrong here
TF-IDF is a feature transformation, not an exploratory step. It does not directly show vocabulary size or frequency distribution.
- ✓
Plot frequency of each word in a bar chart
Why this is correct
Plotting the frequency of each word in a bar chart directly shows the vocabulary size and the frequency distribution (e.g., Zipfian distribution). This EDA step helps decide vocabulary cutoff by identifying very rare words that can be removed.
- ✗
Generate bigram collocations
Why it's wrong here
Bigram collocations are for detecting phrases, not for basic word frequency. They do not show vocabulary size or frequency distribution.
- ✗
Plot histogram of document lengths
Why it's wrong here
Document length distribution pertains to the number of words per document, not vocabulary size or word frequency.
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