AWS Certified AI PractitionerAI/ML and Generative AI FundamentalsEasy
A retail company wants to analyze customer reviews to automatically categorize them as positive, negative, or neutral. Which type of machine learning task is most appropriate for this requirement?
- ADimensionality Reduction
- BClustering
- CClassification
- DRegression
Show answer & explanationAnswer & explanation
Correct answer: C. Classification
Categorizing customer reviews into predefined categories (positive, negative, neutral) is a classic example of a classification task. The model learns from labeled data to assign new, unseen reviews to one of these discrete classes.
Why the other options are wrong
- A. Dimensionality reduction aims to reduce the number of features in a dataset, not to categorize data.
- B. Clustering is an unsupervised learning task that groups similar data points without predefined labels, whereas this problem has specific categories.
- D. Regression is used for predicting continuous numerical values, not discrete categories.
Classification (ML)
A supervised machine learning task that involves predicting a discrete class label for a given input data point.
- Output is a category or class (e.g., spam/not spam, positive/negative sentiment).
- Requires labeled training data.
- Examples: sentiment analysis, image recognition, medical diagnosis.
Memory trick: ML 'tasks' are about 'predicting' different 'types' of outcomes.