Remove appx DBSCAN impl and replace with type aliases (rust-ml#298)

* Remove appx DBSCAN impl and replace with type aliases

* Remove appx DBSCAN example and benchmark

Author: YuhanLiin

algorithms/linfa-clustering/Cargo.toml

@@ -37,7 +37,7 @@ num-traits = "0.2"
 rand_xoshiro = "0.6"
 space = "0.12"
 thiserror = "1.0"
-partitions = "0.2.4"
+#partitions = "0.2.4" This one will break in a future version of Rust and has no replacement
 linfa = { version = "0.6.1", path = "../.." }
 linfa-nn = { version = "0.6.1", path = "../linfa-nn" }
 noisy_float = "0.2.0"
@@ -59,10 +59,6 @@ harness = false
 name = "dbscan"
 harness = false
 
-[[bench]]
-name = "appx_dbscan"
-harness = false
-
 [[bench]]
 name = "gaussian_mixture"
 harness = false

algorithms/linfa-clustering/README.md

@@ -14,15 +14,13 @@ You can find a roadmap (and a selection of good first issues)
 `linfa-clustering` currently provides implementation of the following clustering algorithms, in addition to a couple of helper functions: 
 - K-Means
 - DBSCAN
-- Approximated DBSCAN
+- Approximated DBSCAN (Currently an alias for DBSCAN, due to its superior performance)
 - Gaussian Mixture Model
 
 
 Implementation choices, algorithmic details and a tutorial can be found 
 [here](https://docs.rs/linfa-clustering).
 
-**WARNING:** Currently the Approximated DBSCAN implementation is slower than the normal DBSCAN implementation. Therefore DBSCAN should always be used over Approximated DBSCAN.
-
 ## BLAS/Lapack backend
 We found that the pure Rust implementation maintained similar performance to the BLAS/LAPACK version and have removed it with this [PR](https://github.com/rust-ml/linfa/pull/257). Thus, to reduce code complexity BLAS support has been removed for this module.
 

algorithms/linfa-clustering/benches/appx_dbscan.rs

@@ -15,20 +15,28 @@
 //! Right now `linfa-clustering` provides the following clustering algorithms:
 //! * [K-Means](KMeans)
 //! * [DBSCAN](Dbscan)
-//! * [Approximated DBSCAN](AppxDbscan)
+//! * [Approximated DBSCAN](AppxDbscan) (Currently an alias for DBSCAN, due to its superior
+//! performance)
 //! * [Gaussian-Mixture-Model](GaussianMixtureModel)
 //! * [OPTICS](OpticsAnalysis)
 //!
 //! Implementation choices, algorithmic details and tutorials can be found in the page dedicated to the specific algorithms.
-mod appx_dbscan;
 mod dbscan;
 mod gaussian_mixture;
 #[allow(clippy::new_ret_no_self)]
 mod k_means;
 mod optics;
 
-pub use appx_dbscan::*;
 pub use dbscan::*;
 pub use gaussian_mixture::*;
 pub use k_means::*;
 pub use optics::*;
+
+// Approx DBSCAN is currently an alias for DBSCAN, due to the old Approx DBSCAN implementation's
+// lower performance and outdated dependencies
+
+use linfa_nn::distance::L2Dist;
+pub type AppxDbscanValidParams<F, N> = DbscanValidParams<F, L2Dist, N>;
+pub type AppxDbscanParams<F, N> = DbscanParams<F, L2Dist, N>;
+pub type AppxDbscanParamsError = DbscanParamsError;
+pub type AppxDbscan = Dbscan;