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Citation

Normal footnote1.

Nash's Paper2.

Code

from toyml.clustering.kmeans_clustering import Kmeans
 
 
def run():
    k: int = 2
    dataset = [[1.0, 2], [1, 4], [1, 0], [10, 2], [10, 4], [10, 0]]
 
    kmeans = Kmeans(dataset, k)
    kmeans.fit()
    kmeans.print_cluster()
    test_input = [0.0, 0.0]
    test_output = kmeans.predict(test_input)
    print(f"input: {test_input} -> output: {test_output}")
 
run()

Math

AUC⁡(f)=∑t0∈D0∑t1∈D11[f(t0)<f(t1)]∣D0∣⋅∣D1∣\operatorname{AUC}(f)=\frac{\sum_{t_0 \in \mathcal{D}^0} \sum_{t_1 \in \mathcal{D}^1} \mathbf{1}\left[f\left(t_0\right)<f\left(t_1\right)\right]}{\left|\mathcal{D}^0\right| \cdot\left|\mathcal{D}^1\right|}

References

Nash, John. “Equilibrium Points in N-Person Games.” Proceedings of the National Academy of Sciences 36, no. 1 (1950): 48–49.

Footnotes

  1. This is a normal footnote. ↩

  2. John Nash, “Equilibrium Points in N-Person Games,” Proceedings of the National Academy of Sciences 36, no. 1 (1950): 48–49.↩

Written by

Mathew Shen

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Wed Jul 24 2024

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