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Looks how are NA distributed in each subset
NA
evaluate_na(i, pheno)
The optimum value to reduce
list of numeric indices of the data.frame
Data.frame
Other functions to evaluate samples: evaluate_entropy(), evaluate_independence(), evaluate_index(), evaluate_mad(), evaluate_mean(), evaluate_orig(), evaluate_sd()
evaluate_entropy()
evaluate_independence()
evaluate_index()
evaluate_mad()
evaluate_mean()
evaluate_orig()
evaluate_sd()
Other functions to evaluate categories: evaluate_entropy(), evaluate_independence()
Other functions to evaluate numbers: evaluate_mad(), evaluate_mean(), evaluate_sd()
samples <- 10 m <- matrix(rnorm(samples), nrow = samples) m[sample(seq_len(samples), size = 5), ] <- NA # Some NA i <- create_subset(samples, 3, 4) # random subsets evaluate_na(i, m)
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