sk_cluster: SKLearn Clustering

In abresler/sklearn: sklearn port

SKLearn Clustering

Description

Functions for unsupervised clustering algorithms.

Usage

sk_cluster()

Details

• clustering functions

• clustering examples

Value

python object

Examples

clusterer <- sk_cluster()

## DBSCAN

dbscan <- clusterer$DBSCAN(algorithm = "auto", leaf_size = 10L)
X <- iris %>% select_if(is.numeric) %>% as_tibble()
model <- dbscan$fit(X = X)
clusters <-
model$fit_predict(X = X) + 1
df <-
iris %>%
mutate(cluster = clusters) %>%
as_tibble()
df

## K-Means
X <- iris %>% select_if(is.numeric) %>% as_tibble()
iris_clusters <- clusterer$k_means(X = X, n_clusters = 3L,
precompute_distances = T, init = "random", max_iter = 100L,
return_n_iter = T)
iris_clusters
kmeans_centroids <-
iris_clusters[[1]] %>%
t() %>%
as_tibble()
cluster <- iris_clusters[[2]] + 1
intertia <- iris_clusters[[3]]
df_iris <-
iris %>%
as_tibble() %>%
mutate(cluster)
tibble(intertia, centroids = list(kmeans_centroids),
dataClusters = list())

abresler/sklearn documentation built on July 27, 2023, 7:07 a.m.