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MLA-C01 · Question #26
MLA-C01 Question #26: Real Exam Question with Answer & Explanation
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Data Preparation for Machine Learning
Question
A company wants to predict the success of advertising campaigns by considering the color scheme of each advertisement. An ML engineer is preparing data for a neural network model. The dataset includes color information as categorical data. Which technique for feature engineering should the ML engineer use for the model?
Options
- AApply label encoding to the color categories. Automatically assign each color a unique integer.
- BImplement padding to ensure that all color feature vectors have the same length.
- CPerform dimensionality reduction on the color categories.
- DOne-hot encode the color categories to transform the color scheme feature into a binary matrix.
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Topics
#Feature Engineering#Categorical Data Encoding#One-hot Encoding#Neural Networks Data Preparation