r - 训练期间的节点排序算法(R : randomForest)

Question

随机森林实现需要对每棵树的每个节点处的训练样本值进行排序，以确定要设置的最佳阈值。我想知道 R 包 randomForest 使用哪种排序算法。我找不到任何相关信息。非常感谢!

Answer 1

randomForest 包为 Breiman 和 Cutler 的 Fortran 程序提供了一个 R 接口(interface)(有关更多详细信息，请参阅 here)。
Fortran 代码可用 here .
用于排序的子例程如下(基于“改进的霍尔快速排序”):

    subroutine quicksort(v,iperm,ii,jj,kk)
c
c   puts into iperm the permutation vector which sorts v into
c   increasing order.  only elementest from ii to jj are considered.
c   array iu(k) and array il(k) permit sorting up to 2**(k+1)-1 elements
c
c   this is a modification of acm algorithm #347 by r. c. singleton,
c   which is a modified hoare quicksort.
c
    real v(kk),vt,vtt
    integer t,tt,iperm(kk),iu(32),il(32)
    integer ii,jj,kk,m,i,j,k,ij,l
c
    m=1
    i=ii
    j=jj
 10     if (i.ge.j) go to 80
 20     k=i
    ij=(j+i)/2
    t=iperm(ij)
    vt=v(ij)
    if (v(i).le.vt) go to 30
    iperm(ij)=iperm(i)
    iperm(i)=t
    t=iperm(ij)
    v(ij)=v(i)
    v(i)=vt
    vt=v(ij)
 30     l=j
    if (v(j).ge.vt) go to 50
    iperm(ij)=iperm(j)
    iperm(j)=t
    t=iperm(ij)
    v(ij)=v(j)
    v(j)=vt
    vt=v(ij)
    if (v(i).le.vt) go to 50
    iperm(ij)=iperm(i)
    iperm(i)=t
    t=iperm(ij)
    v(ij)=v(i)
    v(i)=vt
    vt=v(ij)
    go to 50
 40     iperm(l)=iperm(k)
    iperm(k)=tt
    v(l)=v(k)
    v(k)=vtt
 50     l=l-1
    if (v(l).gt.vt) go to 50
    tt=iperm(l)
    vtt=v(l)
 60     k=k+1
    if (v(k).lt.vt) go to 60
    if (k.le.l) go to 40
    if (l-i.le.j-k) go to 70
    il(m)=i
    iu(m)=l
    i=k
    m=m+1
    go to 90
 70     il(m)=k
    iu(m)=j
    j=l
    m=m+1
    go to 90
 80     m=m-1
    if (m.eq.0) return
    i=il(m)
    j=iu(m)
 90     if (j-i.gt.10) go to 20
    if (i.eq.ii) go to 10
    i=i-1
 100    i=i+1
    if (i.eq.j) go to 80
    t=iperm(i+1)
    vt=v(i+1)
    if (v(i).le.vt) go to 100
    k=i
 110    iperm(k+1)=iperm(k)
    v(k+1)=v(k)
    k=k-1
    if (vt.lt.v(k)) go to 110
    iperm(k+1)=t
    v(k+1)=vt
    go to 100
    end