UnixJunkie/orf
OCaml Random Forests
This helps data scientists and machine learning engineers quickly build robust predictive models. You input datasets with categorical features (like user demographics or product types) that have been converted into numerical form. The output is a highly accurate classification or regression model that makes predictions without overfitting, even with default settings. It's ideal for practitioners who need reliable machine learning predictions and want to avoid complex model tuning.
No commits in the last 6 months.
Use this if you need a dependable, fast-to-train model for classification or regression tasks using sparse integer (one-hot encoded categorical) features.
Not ideal if your task requires predicting values beyond the range seen in your training data, such as discovering extreme outliers.
Stars
8
Forks
1
Language
OCaml
License
—
Category
Last pushed
Jan 10, 2023
Commits (30d)
0
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