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NEWS

• Removed dependence on the /bits/stdc++.h header.

• Various refactoring by m-muecke

• HDBSCAN gained parameter cluster_selection_epsilon to implement clusters selected from Malzer and Baum (2020).
• Functions ncluster() and nnoise() were added.
• hullplot now() marks noise as x.
• Added clplot().
• pointdensity now also accepts a dist object as input and has the new type “gaussian” to calculate a Gaussian kernel estimate.
• Added the DBCV index.

• extractFOCS: Fixed total_score.
• Rewrote minimal spanning tree code.

• dbscan has now tidymodels tidiers (glance, tidy, augment).
• kNNdistplot can now plot a range of k/minPts values.
• added stats::nobs methods for the clusterings.
• kNN and frNN now contains the used distance metric.

• dbscan component dist was renamed to metric.
• Removed redundant sort in kNNdistplot (reported by Natasza Szczypien).
• Refactoring use anyNA(x) instead of any(is.na(x)) and many more (by m-muecke).
• Reorganized the C++ source code.
• README now uses bibtex.
• Tests use now testthat edition 3 (m-muecke).

• point_density checks now for missing values (reported by soelderer).
• Removed C++11 specification.
• ANN.cpp: fixed Rprintf warning.

• kNNdistplot gained parameter minPts.
• dbscan now retains information on distance method and border points.
• HDBSCAN now supports long vectors to work with larger distance matrices.
• conversion from dist to kNN and frNN is now more memory efficient. It does no longer coerce the dist object into a matrix of double the size, but extract the distances directly from the dist object.
• Better description of how predict uses only Euclidean distances and more error checking.
• The package now exports a new generic for as.dendrogram().

• is.corepoint() now uses the correct epsilon value (reported by Eng Aun).
• functions now check for cluster::dissimilariy objects which have class dist but missing attributes.

• is.corepoint() for DBSCAN.
• coredist() and mrdist() for HDBSCAN.
• find connected components with comps().

• reachability plot now shows all undefined distances as a dashed line.

• memory leak in mrd calculation fixed.

• We use now roxygen2.

• Added predict for hdbscan (as suggested by moredatapls)

• LOF: fixed numerical issues with k-nearest neighbor distance on Solaris.

• Fixed description of k in knndistplot and added minPts argument.
• Fixed bug for tied distances in lof (reported by sverchkov).

• lof: the density parameter was changes to minPts to be consistent with the original paper and dbscan. Note that minPts = k + 1.

• Improved speed of LOF for large ks (following suggestions by eduardokapp).
• kNN: results is now not sorted again for kd-tree queries which is much faster (by a factor of 10).
• ANN library: annclose() is now only called once when the package is unloaded. This is in preparation to support persistent kd-trees using external pointers.
• hdbscan lost parameter xdist.

• removed dependence on methods.
• fixed problem in hullplot for singleton clusters (reported by Fernando Archuby).
• GLOSH now also accepts data.frames.
• GLOSH returns now 0 instead of NaN if we have k duplicate points in the data.

• kNN and frNN gained parameter query to query neighbors for points not in the data.
• sNN gained parameter jp to decide if the shared NN should be counted using the definition by Jarvis and Patrick.

• kNNdist gained parameter all to indicate if a matrix with the distance to all nearest neighbors up to k should be returned.

• kNNdist now correctly returns the distances to the kth neighbor (reported by zschuster).
• dbscan: check eps and minPts parameters to avoid undefined results (reported by ArthurPERE).

• pointdensity was double counting the query point (reported by Marius Hofert).

• OPTICS now calculates eps if it is omitted.

• Example now only uses igraph conditionally since it is unavailable on Solaris (reported by B. Ripley).

• Fixed problem with constant name on Solaris in ANN code (reported by B. Ripley).

• HDBSCAN was added.
• extractFOSC (optimal selection of clusters for HDBSCAN) was added.
• GLOSH outlier score was added.
• hullplot uses now filled polygons as the default.
• hullplot now used PCA if the data has more than 2 dimensions.
• Added NN superclass for kNN and frNN with plot and with adjacencylist().
• Added shared nearest neighbor clustering as sNNclust() and sNN to calculate the number of shared nearest neighbors.
• Added pointdensity function.
• Unsorted kNN and frNN can now be sorted using sort().
• kNN and frNN now also accept kNN and frNN objects, respectively. This can be used to create a new kNN (frNN) with a reduced k or eps.
• Datasets added: DS3 and moon.

• Improved interface for dbscan() and optics(): … it now passed on to frNN.
• OPTICS clustering extraction methods are now called extractDBSCAN and extractXi.
• kNN and frNN are now objects with a print function.
• dbscan now also accepts a frNN object as input.
• jpclust and sNNclust now return a list instead of just the cluster assignments.

• The package has now a vignette.
• Jarvis-Patrick clustering is now available as jpclust().
• Improved interface for dbscan() and optics(): … is now passed on to frNN.
• OPTICS clustering extraction methods are now called extractDBSCAN and extractXi.
• hullplot uses now filled polygons as the default.
• hullplot now used PCA if the data has more than 2 dimensions.
• kNN and frNN are now objects with a print function.
• dbscan now also accepts a frNN object as input.

• Added hullplot to plot a scatter plot with added convex cluster hulls.
• OPTICS: added a predecessor correction step that is used by the ELKI implementation (Matt Piekenbrock).

• Fixed a memory problem in frNN (reported by Yilei He).

• OPTICSXi is now implemented (thanks to Matt Piekenbrock).
• DBSCAN now also accepts MinPts (with a capital M) to be compatible with the fpc version.
• DBSCAN objects are now also of class db scan_fast to avoid clashes with fpc.
• DBSCAN and OPTICS have now predict functions.
• Added test for unhandled NAs.
• Fixed LOF for more than k duplicate points (reported by Samneet Singh).

• OPTICS: fixed second bug reported by Di Pang
• all methods now also accept dist objects and have a search method “dist” which precomputes distances.

• OPTICS: fixed bug with first observation reported by Di Pang
• OPTICS: clusterings can now be extracted using optics_cut

• added tests (testthat).
• input data is now checked if it can safely be coerced into a numeric matrix (storage.mode double).
• fixed self matches in kNN and frNN (now returns the first NN correctly).

• Added weights to DBSCAN.

• Added kNN interface.
• Added frNN (fixed radius NN) interface.
• Added LOF.
• Added OPTICS.
• All algorithms check now for interrupt (CTRL-C/Esc).
• DBSCAN now returns a list instead of a numeric vector.

• DBSCAN: Improved speed by avoiding repeated sorting of point ids.
• Added linear NN search option.
• Added fast calculation for kNN distance.
• fpc and microbenchmark are now used conditionally in the examples.

• initial release

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