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, ',',