實(shí)戰(zhàn)醫(yī)學(xué)統(tǒng)計(jì)機(jī)器學(xué)習(xí)之關(guān)聯(lián)規(guī)則

犀 鯊魚和?(女性)n(月收入>1W)→ associationrulemining ARM是對樣本隱含規(guī)律的歸納和總結(jié)，不能用于預(yù)測只能做知識發(fā)現(xiàn)

A→(A1^A2……An)→前項(xiàng)前項(xiàng)→置信度提升度只有S>SminC>Cmin同時(shí)滿足才是有效的規(guī)則，S、C代表有無效，L代表有無實(shí)際意義 C{A→B}=NA→B/NA=S{A→B}/

L{A→B}=S{A→B}/S{A}*L<1互斥，負(fù)關(guān)聯(lián)L=1無研究意義L>1共生，正關(guān)聯(lián)例：血壓實(shí)際測量值[100，200]轉(zhuǎn)化 [100，140]收縮壓正常，賦值0否1 (140，200]收縮壓偏高，賦值0否1 歲20例先心病患兒，截取3個(gè)特征屬性，ASDVSDPDA，計(jì)算關(guān)聯(lián)規(guī)則的支持度 置信度C{asd→vsd}=Nasd→vsd/Nasd=S{asd→vsd} L{asd→vsd}=S{asd→vsd}/S{asd}* 例：省醫(yī)臨床診斷數(shù)據(jù)40例，abcde5個(gè)特征屬性，分析關(guān)聯(lián)規(guī)則，定義剪枝(prune)和合并例 Sb=0.75Sc=1.0Sd=0.2設(shè)置S閾值 prune過濾掉ad，合并bce特征屬性組合成規(guī) 設(shè)置C閾值prune過濾<80%的組合，jion最終規(guī)則Cb^e→c=1.0Cc→e=1.0Ce→b=1.0，進(jìn)一步可計(jì)算Earlychildhoodcaries 言、出生低體重、父母健康意識薄弱Ivan?evi?V,Tu?ekI,Tu?ekJ,etal.Usingassociationruleminingtoidentifyriskfactorsforearlychildhoodcaries[J].ComputerMethods&ProgramsinBiomedicine,2015,122(2):175-ARMisperformedontheECCdat341casesand36categoricalPresence:S≥0.05，C≥0.6Absence:S≥0.15，C

篩查項(xiàng)目中一般設(shè)置S<0.1及更低，但會(huì)產(chǎn)生非常多的關(guān)聯(lián)規(guī)則數(shù) Apriorialgorithm+RAfterpruning,thereremained15PR1rulesand6306PR2SCL采用clementine ShahrakiAD,SafdariR,GahfarokhiHH,etal.TheUsageofAssociationRuleMiningtoIdentifyInfluencingFactorsonDeafnessAfterBirth[J].ActaInformaticaMedica,2015,Supportandconfidencehavebeenmentionedastwocriteriaforcharismaticrulethatrepresentutilityandcertaintyofrule.Ingeassociationruleisconsideredincaseitmeetsminimumsupportandminimumconfidencethreshold,thatthesethresholdsaredeterminedbyaspecialized .Amoreaccuratedefinitionfortheaforementionedtermsisasfollow:ifAandBenjoysupport(S),S%ofthetransactionswillincludeunionofAandB.ifAandBenjoyconfidence(C),C%ofthetransactionswillincludeunionofAandB.Iftheruleswithconfidenceabove60%andsupportabove7%areconsidered,fiverulesbelowwillbeobtained.

流vs離散網(wǎng)絡(luò)圖；離散vsvsSminCmin提高，rules變少；默認(rèn)S=0.1，規(guī)則C=0.8，前項(xiàng)87.4%同時(shí)凍肉，啤酒+罐頭蔬菜+凍肉占總?cè)藬?shù)15.5%，采用此 數(shù)據(jù)格式要求比較尷尬，要求數(shù)據(jù)格式要求比較尷尬，要求item設(shè)置S≥0.1，C

117S(0.1~0.7)，C(0.14~1),L(0.714~10)同 同 發(fā)生率同 (指環(huán)王2)同生關(guān)系 C S LR #安裝Matrix包后創(chuàng)建稀疏矩陣sparsematrixgroceries<-read.transactions("groceries.csv",sep=",")#S直方圖，S降序itemFrequencyPlot(groceries,support=0.1)itemFrequencyPlot(groceries,topN=20)image(sample(groceries,100))#Rgroceryrules<-apriori(groceries,parameter=list(support=0.006,confidence