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GitHub / Paul-Andrew-15 / ICC-2023-Worldcup-prediction

Predicting the champion of the 2023 Cricket World Cup through the implementation of the Random Forest algorithm.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Paul-Andrew-15%2FICC-2023-Worldcup-prediction

Stars: 4
Forks: 1
Open Issues: 0

License: mit
Language: Jupyter Notebook
Repo Size: 1.06 MB
Dependencies: 0

Created: 9 months ago
Updated: 5 months ago
Last pushed: 8 months ago
Last synced: 4 months ago

Commit Stats

Commits: 5
Authors: 2
Mean commits per author: 2.5
Development Distribution Score: 0.2
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/Paul-Andrew-15/ICC-2023-Worldcup-prediction

Topics: algorithms, artificial-intelligence, cricket, datasets, jupyter-notebook, knearest-neighbors, machine-learning, naive-bayes-algorithm, random-forest, sckit-learn, support-vector-machines, worldcup2023

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