Plot all bi-variable GMM (clusters) with the colors corresponding to the assigned user profile. This shows which clusters correspond to which user profile, and the proportion of every user profile.

Usage

plot_model_clusters(
  subsets_clustering = list(),
  clusters_definition = list(),
  profiles_ratios,
  log = TRUE
)

Arguments

subsets_clustering: list with clustering results of each subset (direct output from function cluser_sessions())
clusters_definition: list of tibbles with clusters definitions (direct output from function define_clusters()) of each sub-set
profiles_ratios: tibble with columns profile and ratio
log: logical, whether to transform ConnectionStartDateTime and ConnectionHours variables to natural logarithmic scale (base = exp(1)).

Value

ggplot2

Examples

library(dplyr)

# Select working day sessions (`Timecycle == 1`) that
# disconnect the same day (`Disconnection == 1`)
sessions_day <- evprof::california_ev_sessions_profiles %>%
  filter(Timecycle == "Workday") %>%
  sample_frac(0.05)
plot_points(sessions_day, start = 3)


# Identify two clusters
sessions_clusters <- cluster_sessions(
  sessions_day, k=2, seed = 1234, log = TRUE
)

# Plot the clusters found
plot_bivarGMM(
  sessions = sessions_clusters$sessions,
  models = sessions_clusters$models,
  log = TRUE, start = 3
)


# Define the clusters with user profile interpretations
clusters_definitions <- define_clusters(
  models = sessions_clusters$models,
  interpretations = c(
    "Connections during all day (high variability)",
    "Connections during working hours"#'
  ),
  profile_names = c("Visitors", "Workers"),
  log = TRUE
)

# Create a table with the connection GMM parameters
connection_models <- get_connection_models(
  subsets_clustering = list(sessions_clusters),
  clusters_definition = list(clusters_definitions)
)

# Plot all bi-variable GMM (clusters) with the colors corresponding
# to their assigned user profile
plot_model_clusters(
  subsets_clustering = list(sessions_clusters),
  clusters_definition = list(clusters_definitions),
  profiles_ratios = connection_models[c("profile", "ratio")]
)