In NiklasCarlos1994/batchanalytics: Functions That Represent Metrics For Analysing Batching Behavior

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#load packages
library(batchanalytics)
library(bupaR)
library(bamalog)
library(tidyr)
library(readr)
library(lubridate)

evaltuate batch mining

#input data

setwd("C:\\Users\\Niklas\\Desktop\\BachelorArbeit\\EventLogs\\real_world_event_logs")


csv_log <- read.csv("hospital_billing_ready_for_analyis.csv")

 seq_tolerated_gap_list <- seq_tolerated_gap_list_generator(task_log = csv_log,
                                                             seq_tolerated_gap_value = 0)


 subsequence_list <- enumerate_subsequences(csv_log, 0)

  result_log <- detect_batching(task_log = csv_log,
                                act_seq_tolerated_gap_list = seq_tolerated_gap_list,
                                timestamp_format = "yyyy-mm-dd hh:mm:ss",
                                numeric_timestamps = FALSE,
                                log_and_model_based = TRUE,
                                subsequence_list = subsequence_list,
                                subsequence_type = "enum",
                                # use `mine` to use frequence sequence mining
                                # subsequence_type = "mine",
                                within_case_seq_tolerated_gap = 0,
                                between_cases_seq_tolerated_gap = 0,
                                show_progress = F)

result_log <- my_detect_batching(task_log)

head(result_log)

#bupaR api


result_log <- detect_batching_log(patients, show_progress = F)

NiklasCarlos1994/batchanalytics documentation built on Dec. 17, 2021, 5:25 a.m.