Description Usage Arguments Value Examples
Find the nearest hit/miss matrices
1 2 | find.neighbors(attr.mat, pheno.class, metric = "manhattan",
method = "multisurf", k = 0, sd.vec = NULL, sd.frac = 0.5)
|
attr.mat |
m x p matrix of m instances and p attributes |
pheno.class |
length m vector of binary class status (usually -1/1) |
metric |
for distance matrix between instances ( |
method |
neighborhood method [ |
k |
number of constant nearest hits/misses for |
sd.frac |
multiplier of the standard deviation of the distances when subtracting from average for SURF or multiSURF. The multiSURF default is sd.frac=0.5: mean - sd/2 |
return variable (hitmiss.list) is a two-element: hitmiss.list[[1]] (hits) and hitmiss.list[[2]] (misses). Each list has two columns: $Ri_idx is the first column (instances) in both lists. The second column is $hit_idx (nearest hits for the first column instance) for list [[1]] and $miss_idx (nearest misses) for list [[2]].
1 2 3 4 5 6 7 | #See vignette("STIRvignette")
RF.method = "multisurf"
metric <- "manhattan"
neighbor.idx.observed <- find.neighbors(predictors.mat, pheno.class, k = 0, method = RF.method)
results.list <- stir(predictors.mat, neighbor.idx.observed, k = k, metric = metric, method = RF.method)
t_sorted_multisurf <- results.list$STIR_T
t_sorted_multisurf$attribute <- rownames(t_sorted_multisurf)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.