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feat: documents KNN Classifier

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Volodymyr Orlov
2020-08-27 19:47:11 -07:00
parent 762bc3d765
commit dcf636a5f1
3 changed files with 91 additions and 7 deletions
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src/lib.rs
+6 -6
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@@ -6,12 +6,12 @@
//! Welcome to SmartCore library, the most complete machine learning library for Rust!
//!
//! In SmartCore you will find implementation of these ML algorithms:
//! * Regression: Linear Regression (OLS), Decision Tree Regressor, Random Forest Regressor
//! * Classification: Logistic Regressor, Decision Tree Classifier, Random Forest Classifier, Unsupervised Nearest Neighbors (KNN)
//! * Clustering: K-Means
//! * Matrix decomposition: PCA, LU, QR, SVD, EVD
//! * Distance Metrics: Euclidian, Minkowski, Manhattan, Hamming, Mahalanobis
//! * Evaluation Metrics: Accuracy, AUC, Recall, Precision, F1, Mean Absolute Error, Mean Squared Error, R2
//! * __Regression__: Linear Regression (OLS), Decision Tree Regressor, Random Forest Regressor, K Nearest Neighbors
//! * __Classification__: Logistic Regressor, Decision Tree Classifier, Random Forest Classifier, Supervised Nearest Neighbors (KNN)
//! * __Clustering__: K-Means
//! * __Matrix Decomposition__: PCA, LU, QR, SVD, EVD
//! * __Distance Metrics__: Euclidian, Minkowski, Manhattan, Hamming, Mahalanobis
//! * __Evaluation Metrics__: Accuracy, AUC, Recall, Precision, F1, Mean Absolute Error, Mean Squared Error, R2
//!
//! Most of algorithms implemented in SmartCore operate on n-dimentional arrays. While you can use Rust vectors with all functions defined in this library
//! we do recommend to go with one of the popular linear algebra libraries available in Rust. At this moment we support these packages: