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Implementation:DistrictDataLabs Yellowbrick TargetType Utilities

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Domains Data_Science, Utilities
Last Updated 2026-02-08 05:00 GMT

Overview

Target variable type detection utilities providing the TargetType enum and automatic classification of target vectors as single, discrete, or continuous.

Description

The utils.target module provides the TargetType enum with values AUTO, SINGLE, DISCRETE, CONTINUOUS, and UNKNOWN, and the target_color_type function that inspects a target vector to determine its type. This determines whether Yellowbrick visualizers use discrete class colors or a continuous colormap. The threshold for discrete vs continuous is MAX_DISCRETE_CLASSES = 12.

Usage

Import these utilities when building visualizers that need to auto-detect whether to use a categorical or continuous color scheme based on the target variable.

Code Reference

Source Location

Signature

class TargetType(Enum):
    AUTO = "auto"
    SINGLE = "single"
    DISCRETE = "discrete"
    CONTINUOUS = "continuous"
    UNKNOWN = "unknown"

    @classmethod
    def validate(klass, val): ...

def target_color_type(y):
    """Determines the TargetType for a target vector."""

Import

from yellowbrick.utils.target import TargetType, target_color_type

I/O Contract

Inputs

Name Type Required Description
y array-like Yes Target vector to classify

Outputs

Name Type Description
target_type TargetType SINGLE, DISCRETE, CONTINUOUS, or UNKNOWN

Usage Examples

import numpy as np
from yellowbrick.utils.target import target_color_type, TargetType

# Discrete target
y_cls = np.array([0, 1, 2, 0, 1, 2])
print(target_color_type(y_cls))  # TargetType.DISCRETE

# Continuous target
y_reg = np.random.randn(100)
print(target_color_type(y_reg))  # TargetType.CONTINUOUS

# Single value
y_single = None
print(target_color_type(y_single))  # TargetType.SINGLE

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