JuniorTheoryCommon

What happens when this program runs?

Python

import numpy as np
from sklearn.cluster import AgglomerativeClustering

X = np.array([[0], [1], [10], [11]])
model = AgglomerativeClustering(n_clusters=2).fit(X)
print(model.predict(np.array([[2]])))

predict raises AttributeError: this class defines no predict method

Expecting the new point to join the nearest cluster: the merge tree covers only the fitted points, so the class has no predict at all; use fit_predict or labels_.
Expecting NotFittedError: the model is fitted and labels_ is set; the call fails before any check, because the class defines no predict method.

How would you assign new customers to segments found by agglomerative clustering?
Which clustering class in scikit-learn does have a predict method, and what does it compare a new point with?

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JuniorTheoryCommon

What happens when this program runs?

Python

import numpy as np
from sklearn.cluster import AgglomerativeClustering

X = np.array([[0], [1], [10], [11]])
model = AgglomerativeClustering(n_clusters=2).fit(X)
print(model.predict(np.array([[2]])))

predict raises AttributeError: this class defines no predict method

Expecting the new point to join the nearest cluster: the merge tree covers only the fitted points, so the class has no predict at all; use fit_predict or labels_.
Expecting NotFittedError: the model is fitted and labels_ is set; the call fails before any check, because the class defines no predict method.

How would you assign new customers to segments found by agglomerative clustering?
Which clustering class in scikit-learn does have a predict method, and what does it compare a new point with?

Back to questions Open topic in roadmap →Answer it yourself — Quiz