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from misc import *
import math
def onefold(inr,inm,tot,clist,folds,resm):
#inr="a.rid"
#resm="res.m"
#consts used
#clist=[0.0001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 10, 100, 1000]
#folds=4
#tot=316
step = tot // folds
#inm="0.m"
ourb=inr
#splits
print("splitting")
for i in range(folds-1):
inra=ourb
oura="a%d.rid"%i
ourb="b%d.rid"%i
params = "-c %d -i %s -a %s -b %s" %(step,inra,oura,ourb)
split(params)
entries=['0','0']
tmp=take("b0.rid")
put("c0.rid",tmp)
tmp=take("b%d.rid"%(folds-2))
put("a%d.rid"%(folds-1),tmp)
print("merging")
for a in range(folds-1):
tmp=take("a%d.rid"%a)
entries = merge(tmp,entries)
if a<folds-2:
tmp=take("b%d.rid"%(a+1))
tmp = merge(tmp,entries)
else:
tmp = entries;
rid="c%d.rid" %(a+1)
put(rid,tmp)
for i in range(folds):
entries = take("a%d.rid"%a)
inra="c%d.rid"%i
oura="a%d.rid"%i
ourb="b%d.rid"%i
params = "-c %d -i %s -a %s -b %s" %(step,inra,oura,ourb)
split(params)
entries = merge(take("a%d.rid"%a),entries)
print("completed")
wlist=[]
mai=0
#train
for i in range(folds):
for c in clist:
print("folds: %d ,c: %g"%(i,c))
wlist.append("%d-%g"%(i,c))
oum="%d-%g.m" % (i,c)
rid = "a%d.rid"%i
params = "-T -d -m %s -i %s -o %s -c %g" % (inm,rid,oum,c)
train(params)
oup="%d-%g.p"%(i,c)
params = "-P -p -m %s -i %s -o %s" %(oum,inr,oup)
bare(params)
for p in getpred(oup):
mai=max(abs(p),mai);
mai=mai*2;
#inits
D=getpred(oup)
for i in range(len(D)):
D[i]=1/len(D);
mod=getmodel(oum);
for i in range(len(mod)):
mod[i]=0;
while len(wlist)>0:
low=1e20
k=0
P=[]
#find best weak ranker
for w in wlist:
t=0
pr=getpred(w+".p")
for (d,p) in zip(D,pr):
if p<=0:
t+=d
if t<low:
low=t
k=w
P=pr
print(k)
wlist.remove(k)
# cal alpha
r=0;
for (d,p) in zip(D,P):
r+=d*p;
r=r/mai;
a=0.5*math.log((1+r)/(1-r))
#update model
tmod=getmodel(k+".m")
for i in range(len(mod)):
mod[i]+=a*tmod[i];
#update D
for i in range(len(D)):
D[i]=D[i]*math.exp(-a*P[i]);
#normalize D
acc=0;
for d in D:
acc+=d;
for i in range(len(D)):
D[i]/=acc;
#output model
#print(mod)
putmodel(resm,mod)
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