Data Science with Python Certification Data Science with Python Feature Engineering Techniques 5

Question 1

What is the effect of applying np.log1p() instead of np.log() when log-transforming a feature that may contain zeros?

Accepted Answer

It computes log(1 + x), avoiding undefined results for zero values

Answer

np.log1p(x) computes the natural logarithm of (1 + x), which is defined at x=0 and numerically stable for small positive values.

Question 2

In a machine learning pipeline, what is the role of a 'custom transformer' built by subclassing BaseEstimator and TransformerMixin?

Accepted Answer

To create a reusable, pipeline-compatible feature transformation step

Answer

Subclassing BaseEstimator and TransformerMixin lets you implement fit() and transform() methods that integrate seamlessly into sklearn Pipelines and GridSearchCV.

Question 3

What is 'entity embedding' in the context of feature engineering for categorical variables?

Accepted Answer

Learning dense vector representations for categories via a neural network

Answer

Entity embeddings use a neural network's embedding layer to learn low-dimensional dense representations for categorical variables, capturing similarity structure.

Question 4

Which strategy helps mitigate the 'curse of dimensionality' after generating many polynomial interaction features?

Accepted Answer

Applying regularization or feature selection to prune irrelevant features

Answer

After polynomial expansion, regularization (L1/L2) or feature selection methods discard low-signal features, counteracting the sparsity and overfitting risk from high dimensionality.

Question 5

When computing distance-based features (e.g., Euclidean distance between a point and a centroid), what preprocessing step is essential before computing distances?

Accepted Answer

Scaling numerical features to a common range

Answer

Distance metrics are sensitive to feature scale; a feature with range 0–10000 dominates one with range 0–1, so standardization or min-max scaling must be applied first.

Data Science with Python Certification Practice Test

Data Science with Python Certification Practice Test

Data Science with Python Certification Data Science with Python Feature Engineering Techniques 5