cluster_labels_to_dummies()

cluster_labels_to_dummies() is the low-level dummy encoder behind hard_classification_variables(). It maps cluster labels to a (n, K − 1) matrix with one reference category omitted.

Function Usage

cluster_labels_to_dummies(labels, k=None, reference=0)

R / Literature Parameter Mapping

Sequenzo	R / packages	Notes
Omitted-reference dummies	model.matrix(~ factor(labels)) with contrast coding	Helske Table 1 hard classification
Used inside	hard_classification_variables	Low-level omitted-reference encoding for hard classification
Related to	pseudoclass_regression	Pseudoclass builds fixed-K dummies internally because some drawn classes may be absent in a replication

Entry Parameters

Parameter	Required	Type	Description
labels	✓	array-like	Cluster assignment per observation. 0-based or 1-based integers.
k	✗	int / None	Number of clusters. Default: len(unique(labels)).
reference	✗	int	Reference category in sorted unique-label order (0 = first). Omitted from output.

What It Returns

np.ndarray of shape (n, K − 1).

Column j is 1 when the observation belongs to the j-th retained non-reference category after sorting the unique labels and dropping the reference category, and 0 otherwise.

Example

from sequenzo import cluster_labels_to_dummies

dummies = cluster_labels_to_dummies(labels, k=5, reference=0)
print(dummies.shape)

For named DataFrame output, use hard_classification_variables(..., as_dataframe=True) or dummy_column_names() from the same submodule.

Related Helper

dummy_column_names(labels, k=None, reference=0, prefix="C") returns column names for the retained non-reference categories. Names are based on the original label values after sorting and dropping the reference category — for example, if sorted labels are [1, 2, 3, 4, 5] and reference=0, the columns are C_2, C_3, C_4, C_5. It is called internally when hard_classification_variables(..., as_dataframe=True).

Notes

• len(unique(labels)) must equal k.
• Categories are mapped to 0 … K−1 by sorting unique label values before encoding.

Authors

Code: Yuqi Liang

Documentation: Yuqi Liang

References

Helske, S., Helske, J., & Chihaya, G. K. (2024). From sequences to variables: Rethinking the relationship between sequences and outcomes. Sociological Methodology, 54(1), 27–51.