def g(l, returnObject=False):
minError = sys.maxint
for i in range(0,iters):
k1 = cluster.dpmeans(res, l, xVal)
err, xerr = k1.run()
if xerr < minError:
minError = xerr
kmin = k1
if returnObject:
return minError, k1
return minError
def g(l, returnObject=False):
minError = sys.maxint
for i in range(0, iters):
k1 = cluster.dpmeans(res, l, xVal)
err, xerr = k1.run()
if xerr < minError:
minError = xerr
kmin = k1
if returnObject:
return minError, k1
return minError
xval = int(0.20*len(res))
for c in range(1,maxClusters+1):
minError = sys.maxint
with timer.Timer():
for i in range(0,iters):
k1 = cluster.kmeans(res, c, xval)
err, xerr = k1.run()
if xerr < minError:
minError = xerr
writeFile("k-%d-%f1.4"%(c,err), k1)
print 'k-means,',i,',',c,',',minError,',Inter'
sys.stderr.write("kmeans clusters: %d iter: %d \n"%(c,i))
print 'k-means,',c,',',minError,',',
minl = math.log(0.9)
maxl = math.log(math.sqrt(2.0) * dataSpread)
dl = (maxl-minl)/float(maxClusters)
for l in [math.exp(minl + i*dl) for i in range(0, 2*maxClusters)]:
minError = sys.maxint
with timer.Timer():
for i in range(0,iters):
k1 = cluster.dpmeans(res, l, xval)
err, xerr = k1.run()
if xerr < minError:
minError = xerr
writeFile("k-%d-%f1.4"%(c,err), k1)
print 'dp-means,',i,',',l,',',minError,',Inter'
sys.stderr.write("dpmeans lambda: %2.5f iter: %d \n"%(c,i))
print 'dp-means,',l,',',minError,',',
xval = int(0.20 * len(res))
for c in range(1, maxClusters + 1):
minError = sys.maxint
with timer.Timer():
for i in range(0, iters):
k1 = cluster.kmeans(res, c, xval)
err, xerr = k1.run()
if xerr < minError:
minError = xerr
writeFile("k-%d-%f1.4" % (c, err), k1)
print 'k-means,', i, ',', c, ',', minError, ',Inter'
sys.stderr.write("kmeans clusters: %d iter: %d \n" % (c, i))
print 'k-means,', c, ',', minError, ',',
minl = math.log(0.9)
maxl = math.log(math.sqrt(2.0) * dataSpread)
dl = (maxl - minl) / float(maxClusters)
for l in [math.exp(minl + i * dl) for i in range(0, 2 * maxClusters)]:
minError = sys.maxint
with timer.Timer():
for i in range(0, iters):
k1 = cluster.dpmeans(res, l, xval)
err, xerr = k1.run()
if xerr < minError:
minError = xerr
writeFile("k-%d-%f1.4" % (c, err), k1)
print 'dp-means,', i, ',', l, ',', minError, ',Inter'
sys.stderr.write("dpmeans lambda: %2.5f iter: %d \n" % (c, i))
print 'dp-means,', l, ',', minError, ',',
