A small machine learning library aimed at providing simple, concise implementations of machine learning techniques and utilities. It is written in Lisp (using the implementation du jour, Clojure) to maximize expressiveness and enjoyment.

Add the following dependency to your project:

• API Docs

• Artificial neural network
• Decision tree
• Ensemble methods
• K-nearest neighbors
• Linear regression
• Logistic regression
• Naive Bayes
• Random forest

• DBSCAN
• Hierarchical agglomerative clustering
• K-means
• Non-negative matrix factorization

• Classifying handwritten digits with an artificial neural network
• DBSCAN example
• Decision tree example
• Hierarchical agglomerative clustering example
• K-means example
• Predicting survival on the Titanic with logistic regression

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