Association Analysis
Wanyu(Crystal) Lee
5/6/2020
setwd('C://Users/wanyu/Documents/Healthcare/Case 4')
library(plyr)
library(tidyverse)## Warning: package 'tidyverse' was built under R version 3.6.3## -- Attaching packages ---------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.3.1 v purrr 0.3.3
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## x dplyr::summarize() masks plyr::summarize()library(arules)## Loading required package: Matrix##
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## reorder.hclust gcluslibrary(RColorBrewer)
library(kableExtra)##
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library(readr)
library(magrittr)##
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## col_factorpatients_dummies = read.csv('patients_clean_new.csv')
head(patients_dummies)## Patient.ID Mortality..1..death. BEHAV_AdjustmentStress BEHAV_Affective_A
## 1 1 0 0 0
## 2 2 0 0 0
## 3 3 0 0 0
## 4 4 0 0 0
## 5 5 0 0 0
## 6 6 0 0 0
## BEHAV_Affective_B BEHAV_Anxiety_Phobia BEHAV_Ocd_Adhd BEHAV_Other_Nos_A
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## BEHAV_Other_Nos_B BEHAV_Personality_Conduct BEHAV_Psychosis
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## BEHAV_Substance_Abuse CHEST_Airway_Lungs_A CHEST_Airway_Lungs_B
## 1 0 1 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## CHEST_Chest_Wall_A CHEST_Chest_Wall_B CHEST_Complication CHEST_Lung
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## CHEST_Metastatic CHEST_Other_Nec CHEST_Other_Nos_A CHEST_Other_Nos_B
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## CHEST_Pers_Fam_Hx_Ds CHEST_Pleural CHEST_Pneumonia CHEST_Screening
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## CHEST_Status_A CHEST_Status_B CHEST_Uri_A CHEST_Uri_B CVASC_Arterial_A
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## CVASC_Arterial_B CVASC_Cardiac_A CVASC_Cardiac_B CVASC_Complication_A
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 1 0 0
## 6 0 0 0 0
## CVASC_Complication_B CVASC_Heart_Rhythm_A CVASC_Heart_Rhythm_B CVASC_Other
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 1 0
## 6 0 0 0 0
## CVASC_Other_Nos_A CVASC_Other_Nos_B CVASC_Screening_B CVASC_Status_A
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## CVASC_Status_B CVASC_Vascular CVASC_Venous_A CVASC_Venous_B DERMA_Extremity_A
## 1 0 0 0 0 1
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## DERMA_Extremity_B DERMA_Head_Face_Neck_A DERMA_Head_Face_Neck_B
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## DERMA_Imm_Inflam DERMA_Metastatic DERMA_Other_Nos_A DERMA_Other_Nos_B
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## DERMA_Trunk_A DERMA_Trunk_B DERMA_Whole_Body_Nos_B DGL_Unknown
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## ENDOC_MET_Adrenal ENDOC_MET_Brain ENDOC_MET_Diabetes ENDOC_MET_Metabolic_A
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## ENDOC_MET_Metabolic_B ENDOC_MET_Other_Nos ENDOC_MET_Parathyroid
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## ENDOC_MET_Thyroid ENTD__Airway_Lungs ENTD__Benign_A ENTD__Benign_B ENTD__Burn
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## ENTD__Foreign_Body ENTD__Injury_Foreign_Body ENTD__Malignant_A
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## ENTD__Open_Wound ENTD__Other_Nos_A ENTD__Other_Nos_B ENTD__Screening
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## ENTD__Service ENTD__Uncertn EYE___Benign EYE___Cataract
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## EYE___Injury_Foreign_Body EYE___Macular_Degeneration EYE___Malignant
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## EYE___Other_Nos EYE___Sgn_Symp EYE___Status EYE___Vitreous FGENT_Breast_A
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## FGENT_Breast_B FGENT_Complication FGENT_Cx_Uterus_Ovaries_A
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## FGENT_Cx_Uterus_Ovaries_B FGENT_Foreign_Injury_Other FGENT_Other_Nos_A
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## FGENT_Other_Nos_B FGENT_Screening FGENT_Status_A FGENT_Status_B
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## FGENT_Vagina_Ext_Genitalia_A FGENT_Vagina_Ext_Genitalia_B
## 1 0 0
## 2 0 0
## 3 0 0
## 4 0 0
## 5 0 0
## 6 0 0
## GENRL_UNSP_Bacterial GENRL_UNSP_Complication_A GENRL_UNSP_Complication_B
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## GENRL_UNSP_Imm_Inflam GENRL_UNSP_Metastatic GENRL_UNSP_Other_Nos_A
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## GENRL_UNSP_Other_Nos_B GENRL_UNSP_Pers_Fam_Hx_Ds GENRL_UNSP_Screening
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## GENRL_UNSP_Service GENRL_UNSP_Sgn_Symp GENRL_UNSP_Status GENRL_UNSP_Trauma
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## GENRL_UNSP_Viral_A GENRL_UNSP_Viral_B GSTIN_Benign GSTIN_Burn
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## GSTIN_Colorectal_A GSTIN_Colorectal_B GSTIN_Complication_A
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## GSTIN_Complication_B GSTIN_Esophagus_A GSTIN_Esophagus_B GSTIN_Foreign_Body
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## GSTIN_Hepatobiliary_A GSTIN_Hepatobiliary_B GSTIN_Hernia GSTIN_Injury
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## GSTIN_Metastatic GSTIN_Other_Nos_A GSTIN_Other_Nos_B GSTIN_Pers_Fam_Hx_Ds
## 1 0 0 0 0
## 2 0 0 0 1
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 1
## GSTIN_Screening GSTIN_Sgn_Symp GSTIN_Status GSTIN_Stomach_Small_Bowel_A
## 1 0 0 0 0
## 2 0 0 0 1
## 3 1 0 0 0
## 4 1 0 0 0
## 5 1 0 0 0
## 6 0 0 0 0
## GSTIN_Stomach_Small_Bowel_B GSTIN_Upper_Gi_A GSTIN_Upper_Gi_B
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## HEMO__LYMPH_Anemia HEMO__LYMPH_Coagulation_Ds HEMO__LYMPH_Complication
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## HEMO__LYMPH_Leukemia HEMO__LYMPH_Lymphoma HEMO__LYMPH_Metastatic
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## HEMO__LYMPH_Other_Malignancy HEMO__LYMPH_Other_Nos MGENT_Benign_A
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## MGENT_Benign_B MGENT_In_Situ_Uncertn_A MGENT_In_Situ_Uncertn_B
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## MGENT_Malignant_A MGENT_Malignant_B MGENT_Other_Nos MGENT_Screening
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## MSKLT_Complication MSKLT_Extremity_Nos_A MSKLT_Extremity_Nos_B
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## MSKLT_Lower_Ext_Ankle_Foot MSKLT_Lower_Ext_Knee MSKLT_Lower_Ext_Lower_Leg
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## MSKLT_Lower_Ext_Nos MSKLT_Lower_Ext_Thigh MSKLT_Metastatic MSKLT_Other_Nos_A
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## MSKLT_Other_Nos_B MSKLT_Pelvis_Hips MSKLT_Service MSKLT_Spine_Crvcl
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## MSKLT_Spine_Nos MSKLT_Spine_Thor_Lum_Sacr MSKLT_Status_A MSKLT_Status_B
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## MSKLT_Upper_Ext_Arm_Elbow MSKLT_Upper_Ext_Forearm_Wrist MSKLT_Upper_Ext_Hand
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## MSKLT_Upper_Ext_Nos MSKLT_Upper_Ext_Shoulder MSKLT_Upper_Ext_Shoulder_Girdle
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## MSKLT_Upper_Ext_Shoulder_Joint NEURO_Brain_A NEURO_Brain_B
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## NEURO_Cerebrovasc_A NEURO_Cerebrovasc_B NEURO_Cns_Nos_A NEURO_Cns_Nos_B
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## NEURO_Complication_A NEURO_Cord NEURO_Head_A NEURO_Head_B NEURO_Head_Neck
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## NEURO_Other NEURO_Other_Nos_A NEURO_Other_Nos_B NEURO_Periph_Nerves
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## NEURO_Pers_Fam_Hx_Ds NEURO_Service NEURO_Sgn_Symp NEURO_Spine NEURO_Status
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## PREGN_Other_Nos_A PREGN_Other_Nos_B PREGN_Screening PREGN_Service
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## PREGN_Status_A PREGN_Status_B UROLG_GEN_Bladder UROLG_GEN_Complication_A
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## UROLG_GEN_Complication_B UROLG_GEN_Injury UROLG_GEN_Kidney
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## UROLG_GEN_Other_Nos_A UROLG_GEN_Other_Nos_B UROLG_GEN_Pers_Fam_Hx_Ds
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 0 0
## UROLG_GEN_Screening UROLG_GEN_Service UROLG_GEN_Sgn_Symp UROLG_GEN_Status2
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## UROLG_GEN_Status_A UROLG_GEN_Status_B Undefined_Undefined AgeCode_Age_18_39
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## 4 0 0 0 0
## 5 0 0 0 0
## 6 0 0 0 0
## AgeCode_Age_40_49 AgeCode_Age_50_59 AgeCode_Age_60_69 AgeCode_Age_70_74
## 1 0 0 0 1
## 2 0 0 1 0
## 3 0 0 1 0
## 4 0 1 0 0
## 5 0 0 0 1
## 6 0 0 1 0
## AgeCode_Age_75_99 SexCode_Male
## 1 0 0
## 2 0 0
## 3 0 0
## 4 0 1
## 5 0 0
## 6 0 1death = patients_dummies %>%
rename(death=`Mortality..1..death.`) %>%
filter(death==1) %>%
select(-death, -Patient.ID) %>%
summarize_all(mean)
no_death = patients_dummies %>%
rename(death=`Mortality..1..death.`) %>%
filter(death==0) %>%
select(-death, -Patient.ID) %>%
summarize_all(mean)
merge = data.frame(cbind(t(death), t(no_death)))
merge['odds'] = merge[,1]/merge[,2]
top20 = head(merge[order(merge$odds, decreasing = TRUE),],20)
write.csv(top20, 'top20odds.csv')drg_items <- read.transactions('drg_items.csv', format = 'basket', sep=',')
rules = apriori(drg_items, parameter = list(supp=0.05, conf=0.1,maxlen=5, minlen=2))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.1 0.1 1 none FALSE TRUE 5 0.05 2
## maxlen target ext
## 5 rules FALSE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 1063
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[214 item(s), 21271 transaction(s)] done [0.02s].
## sorting and recoding items ... [38 item(s)] done [0.00s].
## creating transaction tree ... done [0.01s].
## checking subsets of size 1 2 3 4 5## Warning in apriori(drg_items, parameter = list(supp = 0.05, conf = 0.1, : Mining
## stopped (maxlen reached). Only patterns up to a length of 5 returned!## done [0.03s].
## writing ... [1824 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].rules = rules[!is.redundant(rules)]
gi <- generatingItemsets(rules)
d <- which(duplicated(gi))
rules = rules[-d]
rules## set of 425 rulesrules_toplift = head(rules[order(quality(rules)$lift, decreasing = TRUE)],20)
plot(rules_toplift, method = "graph", engine = "htmlwidget")top_rules = as(rules_toplift, "data.frame")
top_rules %>%
mutate(rules = gsub("=>", "\n=>", rules)) %>%
kable() %>%
kable_styling(bootstrap_options = "striped",
full_width = F,
position="center")| rules | support | confidence | lift | count |
|---|---|---|---|---|
| {CVASC_Heart_Rhythm_A,GENRL_UNSP_Other_Nos_A} => {HEMO__LYMPH_Other_Nos} | 0.0567439 | 0.4032743 | 2.259760 | 1207 |
| {HEMO__LYMPH_Other_Nos} => {CVASC_Heart_Rhythm_A} | 0.0916271 | 0.5134352 | 2.148167 | 1949 |
| {CHEST_Airway_Lungs_A,ENDOC_MET_Metabolic_A} => {GSTIN_Esophagus_A} | 0.0519017 | 0.3854749 | 1.641200 | 1104 |
| {BEHAV_Substance_Abuse,CVASC_Cardiac_B,ENDOC_MET_Metabolic_A,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.0574491 | 0.7818298 | 1.590351 | 1222 |
| {CVASC_Cardiac_B,ENDOC_MET_Metabolic_A,GENRL_UNSP_Other_Nos_A,SexCode_Male} => {GENRL_UNSP_Service} | 0.0694843 | 0.7701928 | 1.566680 | 1478 |
| {CVASC_Cardiac_B,ENDOC_MET_Diabetes,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.0833529 | 0.7622528 | 1.550529 | 1773 |
| {BEHAV_Substance_Abuse,CVASC_Cardiac_B,CVASC_Other_Nos_B,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.0625264 | 0.7505643 | 1.526753 | 1330 |
| {BEHAV_Substance_Abuse,CVASC_Cardiac_B,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.1065300 | 0.7436823 | 1.512754 | 2266 |
| {CHEST_Airway_Lungs_A,GENRL_UNSP_Other_Nos_A,SexCode_Male} => {BEHAV_Substance_Abuse} | 0.0558977 | 0.6103696 | 1.507918 | 1189 |
| {BEHAV_Substance_Abuse,ENDOC_MET_Diabetes,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.0755489 | 0.7388506 | 1.502925 | 1607 |
| {ENDOC_MET_Diabetes,GSTIN_Esophagus_A} => {ENDOC_MET_Metabolic_A} | 0.0607400 | 0.6434263 | 1.499871 | 1292 |
| {AgeCode_Age_60_69,CVASC_Cardiac_B,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.0508204 | 0.7289278 | 1.482741 | 1081 |
| {ENDOC_MET_Diabetes,ENDOC_MET_Metabolic_A,GENRL_UNSP_Other_Nos_A} => {GENRL_UNSP_Service} | 0.0940717 | 0.7279011 | 1.480652 | 2001 |
| {CVASC_Cardiac_B,GENRL_UNSP_Other_Nos_A,GSTIN_Esophagus_A} => {GENRL_UNSP_Service} | 0.0592826 | 0.7276399 | 1.480121 | 1261 |
| {CVASC_Cardiac_B,ENDOC_MET_Diabetes,ENDOC_MET_Metabolic_A} => {GENRL_UNSP_Service} | 0.0677918 | 0.7166998 | 1.457868 | 1442 |
| {BEHAV_Substance_Abuse,CVASC_Cardiac_B,ENDOC_MET_Diabetes} => {GENRL_UNSP_Service} | 0.0549104 | 0.7161251 | 1.456698 | 1168 |
| {CVASC_Other_Nos_B,GENRL_UNSP_Service,GSTIN_Esophagus_A} => {ENDOC_MET_Metabolic_A} | 0.0573081 | 0.6206721 | 1.446829 | 1219 |
| {BEHAV_Substance_Abuse,CVASC_Cardiac_B,ENDOC_MET_Metabolic_A} => {GENRL_UNSP_Service} | 0.0740915 | 0.7102298 | 1.444707 | 1576 |
| {BEHAV_Substance_Abuse,ENDOC_MET_Metabolic_A,GENRL_UNSP_Other_Nos_A,SexCode_Male} => {GENRL_UNSP_Service} | 0.0603169 | 0.7084484 | 1.441083 | 1283 |
| {CHEST_Airway_Lungs_A,GENRL_UNSP_Service} => {BEHAV_Substance_Abuse} | 0.0902637 | 0.5805866 | 1.434339 | 1920 |
plot(rules_toplift, method = "grouped", aggr.fun='median')
plot(rules, method = "grouped", aggr.fun='median')