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verticapy.machine_learning.memmodel.cluster.KPrototypes.predict_proba

KPrototypes.predict_proba(X: list | ndarray) → ndarray

Predicts the probability of each input to belong to the model clusters.

Parameters

X: ArrayLike

The data on which to make the prediction.

Returns

numpy.array

Probabilities.

Examples

Import the required module.

from verticapy.machine_learning.memmodel.cluster import KMeans

We will use the following attributes:

clusters = [[0.5, 0.6], [1, 2], [100, 200]]

p = 2

Let’s create a model.

model_km = KMeans(clusters, p)

Create a dataset.

data = [[2, 3]]

Compute the predictions.

model_km.predict_proba(data)[0]
Out[31]: array([0.33177263, 0.66395985, 0.00426752])

Important

For this example, a specific model is utilized, and it may not correspond exactly to the model you are working with. To see a comprehensive example specific to your class of interest, please refer to that particular class.