20 #include <raft/cluster/kmeans_types.hpp>
61 const float* sample_weight,
72 const double* sample_weight,
82 const float* sample_weight,
93 const double* sample_weight,
123 const float* centroids,
127 const float* sample_weight,
128 bool normalize_weights,
134 const double* centroids,
138 const double* sample_weight,
139 bool normalize_weights,
144 const float* centroids,
148 const float* sample_weight,
149 bool normalize_weights,
155 const double* centroids,
159 const double* sample_weight,
160 bool normalize_weights,
182 const float* centroids,
190 const double* centroids,
197 const float* centroids,
205 const double* centroids,
Definition: params.hpp:34
void fit_predict(const raft::handle_t &handle, const KMeansParams ¶ms, const float *X, int n_samples, int n_features, const float *sample_weight, float *centroids, int *labels, float &inertia, int &n_iter)
Compute k-means clustering and predicts cluster index for each sample in the input.
raft::cluster::KMeansParams KMeansParams
Definition: kmeans.hpp:30
void transform(const raft::handle_t &handle, const KMeansParams ¶ms, const float *centroids, const float *X, int n_samples, int n_features, float *X_new)
Transform X to a cluster-distance space.
void predict(const raft::handle_t &handle, const KMeansParams ¶ms, const float *centroids, const float *X, int n_samples, int n_features, const float *sample_weight, bool normalize_weights, int *labels, float &inertia)
Predict the closest cluster each sample in X belongs to.
Definition: dbscan.hpp:27
Definition: dbscan.hpp:23