fisher and chi-square analysis

#C1
#-----------------------------------
#  Nível, precision, recall, f-measure
#Proposta, 1, 0.875, 0.933
#AML, 0.966, 0.875, 0.918
#RiMOM, 0.813, 0.813, 0.813

#C2
#-----------------------------------
#  Nível, precision, recall, f-measure
#AML, 0.921, 0.854, 0.886
#Proposta, 0.906, 0.707, 0.794
#RiMOM, 0.707, 0.707, 0.707

#nivel = c("Proposta","AML","RiMOM")
#precision_1 = c(1,0.966,0.813)
#recall_1 = c(0.875,0.875, 0.813)
#f1 = c(0.933,0.918, 0.813)
#df = data.frame(precision,recall,f1)

#proposta, aml - C1
precision_1 = c(1,0.966)
recall_1 = c(0.875,0.875)

df_1 = data.frame(precision_1,recall_1)

chisq.test(df_1)

fisher.test(df_1, alternative = "less")
fisher.test(df_1, alternative = "greater")



#proposta, aml - C2
precision_1 = c(0.906, 0.921)
recall_1 = c(0.707,0.854)

df_1 = data.frame(precision_1,recall_1)

chisq.test(df_1)

fisher.test(df_1, alternative = "less")
fisher.test(df_1, alternative = "greater")


#proposta, rimom - C1
precision_2 = c(1,0.813)
recall_2 = c(0.875,0.813)

df_2 = data.frame(precision_2,recall_2)

chisq.test(df_2)

fisher.test(df_2, alternative = "less")
fisher.test(df_2, alternative = "greater")


#proposta, rimom - C2
precision_2 = c(0.906,0.707)
recall_2 = c(0.707,0.707)

df_2 = data.frame(precision_2,recall_2)

chisq.test(df_2)

fisher.test(df_2, alternative = "less")
fisher.test(df_2, alternative = "greater")


p-value = 0.8333