The data for this experiment was generated, the code belows will generate the data, and perform a single run of each version (HDPMM, HDPMM Global Only, DPMM, DPMM Seperated, vHDPMM), and evaluation.
Note that the data generation is random, thus different results may appear, however the ranking of how well the methods perform are consistent. Also, this is a single run, so no mean or std.
using LinearAlgebra
using Clustering
using Random
function evaluate_pred_groups(GT,pred)
NMI = 0.0
for i=1:length(pred)
group_nmi = mutualinfo(GT[i], pred[i]; normed =true)
if isnan(group_nmi)
group_nmi = 1.0
end
NMI += group_nmi
end
return NMI / length(pred)
end
function evaluate_all_results(GT_Global,
GT_Local,
pred_HDPMM,
pred_HDPMM_GLOBAL,
pred_DPMM,
pred_DPMM_seperated,
pred_vHDPMM_global,
pred_vHDPMM_local,
pred_sep_vHDPMM_global,
pred_sep_vHDPMM_local)
concat_GT_Local = [GT_Local[i] for i=1:length(GT_Local)]
concat_GT_Local = reduce(vcat,concat_GT_Local)
HDPMM_NMI = evaluate_pred_groups(GT_Global, pred_HDPMM)
HDPMM_GLOBAL_NMI = evaluate_pred_groups(GT_Global, pred_HDPMM_GLOBAL)
DPMM_NMI = mutualinfo(concat_GT_Local, pred_DPMM; normed =true)
DPMM_SEP_NMI = evaluate_pred_groups(GT_Local, pred_DPMM_seperated)
vHDPMM_GLOBAL_NMI = evaluate_pred_groups(GT_Global, pred_vHDPMM_global)
vHDPMM_LOCAL_NMI = evaluate_pred_groups(GT_Local, pred_vHDPMM_local)
vHDPMM_SEP_GLOBAL_NMI = evaluate_pred_groups(GT_Global, pred_sep_vHDPMM_global)
vHDPMM_SEP_LOCAL_NMI = evaluate_pred_groups(GT_Local, pred_sep_vHDPMM_local)
println(" HDPMM NMI: $HDPMM_NMI \n
HDPMM Global NMI: $HDPMM_GLOBAL_NMI \n
DPMM NMI: $DPMM_NMI \n
DPMM SEPERATED NMI: $DPMM_SEP_NMI\n
vHDPMM Global NMI: $vHDPMM_GLOBAL_NMI\n
vHDPMM Local NMI: $vHDPMM_LOCAL_NMI
vHDPMM Sep Global NMI: $vHDPMM_SEP_GLOBAL_NMI\n
vHDPMM Sep Local NMI: $vHDPMM_SEP_LOCAL_NMI")
return HDPMM_NMI, HDPMM_GLOBAL_NMI, DPMM_NMI, DPMM_SEP_NMI, vHDPMM_GLOBAL_NMI, vHDPMM_LOCAL_NMI, vHDPMM_SEP_GLOBAL_NMI, vHDPMM_SEP_LOCAL_NMI
end
evaluate_all_results (generic function with 1 method)
using Distributed
addprocs(2)
@everywhere using DPMMSubClusters
@everywhere using VersatileHDPMixtureModels
function run_methods_and_get_results(data,gprior,lprior,dp_prior,ghdp,gdim)
#vHDPM
println("vHDPMM")
vhdpmm_results = vhdp_fit(data,gdim,100.0,1000.0,100.0,gprior,lprior,50)
vhdpmm_global = Dict([i=> create_global_labels(vhdpmm_results[1].groups_dict[i]) for i=1:length(data)])
vhdpmm_local = Dict([i=> vhdpmm_results[1].groups_dict[i].labels for i=1:length(data)])
#HDP-ALL
println("HDP-ALL")
hdp_results = hdp_fit(data,100.0,1000.0,ghdp,50)
hdp_all_global = Dict([i=> create_global_labels(hdp_results[1].groups_dict[i]) for i=1:length(data)])
#HDP-GLOBAL
println("HDP-GLOBAL")
global_pts = Dict([k=>v[1:gdim,:] for (k,v) in data])
hdp_global_results = hdp_fit(global_pts,100.0,1000.0,gprior,50)
hdp_global_global = Dict([i=> create_global_labels(hdp_global_results[1].groups_dict[i]) for i=1:length(data)])
#DPMM-All
println("DPMM-ALL")
all_data = [data[i] for i=1:length(data)]
all_data = reduce(hcat,all_data)
dpmm_all_results = DPMMSubClusters.fit(all_data,dp_prior,100.0,iters = 100, verbose = false)
dpmm_all_local = dpmm_all_results[1]
#DPMM-Seperated
println("DPMM-SEP")
dpmm_seperated_results = [DPMMSubClusters.fit(data[i],dp_prior,100.0,iters = 100, verbose = false) for i=1:length(data)]
dpmm_seperated_local = [dpmm_seperated_results[i][1] for i=1:length(data)]
println("vHDPMM-SEP")
#vHDPM-Seperated
vhdpmm_results = [vhdp_fit(Dict([1=>data[i]]),gdim,100.0,1000.0,100.0,gprior,lprior,50) for i=1:length(data)]
vhdpmm_sep_global = Dict([i=> create_global_labels(vhdpmm_results[i][1].groups_dict[1]) for i=1:length(data)])
vhdpmm_sep_local = Dict([i=> vhdpmm_results[i][1].groups_dict[1].labels for i=1:length(data)])
# return vhdpmm_results
return hdp_all_global,hdp_global_global,dpmm_all_local,dpmm_seperated_local, vhdpmm_global, vhdpmm_local,vhdpmm_sep_global,vhdpmm_sep_local
end
run_methods_and_get_results (generic function with 1 method)
pts,labels = generate_grouped_gaussian_data(20000, 2, 1, 3, 5, 10, false, 25.0, false)
labels_global = Dict([k=> Int.(v[:,1][:]) for (k,v) in labels])
labels_local = Dict([k=> Int.(v[:,2][:]) for (k,v) in labels])
g_prior, l_prior = create_default_priors(2,1,:niw)
g_hdp, _ = create_default_priors(3,0,:niw)
dp_prior = DPMMSubClusters.niw_hyperparams(1.0,
zeros(3),
6,
Matrix{Float64}(I, 3, 3)*1)
DPMMSubClusters.niw_hyperparams(1.0f0, Float32[0.0, 0.0, 0.0], 6.0f0, Float32[1.0 0.0 0.0; 0.0 1.0 0.0; 0.0 0.0 1.0])
hdp_all_global,hdp_global_global,dpmm_all_local,dpmm_seperated_local, vhdpmm_global, vhdpmm_local,vhdpmm_sep_global, vhdpmm_sep_local =
run_methods_and_get_results(pts,g_prior,l_prior,dp_prior,g_hdp,2)
vHDPMM Iteration: 1|| Global Counts: [10]|| iter time: 15.270561933517456 Iteration: 2|| Global Counts: [10]|| iter time: 0.09072518348693848 Iteration: 3|| Global Counts: [10]|| iter time: 0.0733938217163086 Iteration: 4|| Global Counts: [10]|| iter time: 0.07050585746765137 Iteration: 5|| Global Counts: [10]|| iter time: 0.19986987113952637 Iteration: 6|| Global Counts: [11, 11]|| iter time: 1.3131649494171143 Iteration: 7|| Global Counts: [12, 11]|| iter time: 0.11937594413757324 Iteration: 8|| Global Counts: [15, 11]|| iter time: 0.6617319583892822 Iteration: 9|| Global Counts: [16, 11]|| iter time: 0.12209391593933105 Iteration: 10|| Global Counts: [18, 13]|| iter time: 0.08200716972351074 Iteration: 11|| Global Counts: [18, 13]|| iter time: 0.2327899932861328 Iteration: 12|| Global Counts: [19, 14, 19]|| iter time: 0.08287501335144043 Iteration: 13|| Global Counts: [20, 16, 14]|| iter time: 0.43161988258361816 Iteration: 14|| Global Counts: [14, 17, 13]|| iter time: 0.09724116325378418 Iteration: 15|| Global Counts: [14, 18, 13]|| iter time: 0.0930941104888916 Iteration: 16|| Global Counts: [14, 19, 13]|| iter time: 0.10111308097839355 Iteration: 17|| Global Counts: [14, 19, 13]|| iter time: 0.10930585861206055 Iteration: 18|| Global Counts: [14, 20, 13]|| iter time: 0.09452486038208008 Iteration: 19|| Global Counts: [14, 22, 14]|| iter time: 0.10245394706726074 Iteration: 20|| Global Counts: [15, 24, 13]|| iter time: 0.10880899429321289 Iteration: 21|| Global Counts: [15, 25, 13]|| iter time: 0.10081219673156738 Iteration: 22|| Global Counts: [15, 25, 13]|| iter time: 0.10311102867126465 Iteration: 23|| Global Counts: [15, 26, 13]|| iter time: 0.1082468032836914 Iteration: 24|| Global Counts: [15, 27, 13]|| iter time: 0.10729217529296875 Iteration: 25|| Global Counts: [15, 30, 13]|| iter time: 0.10658502578735352 Iteration: 26|| Global Counts: [15, 29, 13]|| iter time: 0.11449289321899414 Iteration: 27|| Global Counts: [15, 30, 13]|| iter time: 0.10986804962158203 Iteration: 28|| Global Counts: [15, 32, 13]|| iter time: 0.10881614685058594 Iteration: 29|| Global Counts: [15, 31, 13]|| iter time: 0.11921811103820801 Iteration: 30|| Global Counts: [15, 34, 13]|| iter time: 0.11265397071838379 Iteration: 31|| Global Counts: [15, 35, 13]|| iter time: 0.11615204811096191 Iteration: 32|| Global Counts: [16, 36, 13]|| iter time: 0.1217489242553711 Iteration: 33|| Global Counts: [16, 38, 13]|| iter time: 0.12449502944946289 Iteration: 34|| Global Counts: [17, 38, 13]|| iter time: 0.1239011287689209 Iteration: 35|| Global Counts: [16, 38, 13]|| iter time: 0.12795805931091309 Iteration: 36|| Global Counts: [16, 44, 13]|| iter time: 0.12409710884094238 Iteration: 37|| Global Counts: [16, 40, 13]|| iter time: 0.12538480758666992 Iteration: 38|| Global Counts: [16, 41, 13]|| iter time: 0.13062810897827148 Iteration: 39|| Global Counts: [16, 41, 13]|| iter time: 0.126708984375 Iteration: 40|| Global Counts: [16, 42, 13]|| iter time: 0.1271190643310547 Iteration: 41|| Global Counts: [16, 35, 13]|| iter time: 0.13089203834533691 Iteration: 42|| Global Counts: [16, 34, 13]|| iter time: 0.11563491821289062 Iteration: 43|| Global Counts: [16, 34, 13]|| iter time: 0.11556410789489746 Iteration: 44|| Global Counts: [16, 33, 13]|| iter time: 0.12364387512207031 Iteration: 45|| Global Counts: [16, 36, 13]|| iter time: 0.11581587791442871 Iteration: 46|| Global Counts: [16, 35, 13]|| iter time: 0.1636059284210205 Iteration: 47|| Global Counts: [16, 36, 13]|| iter time: 0.12881016731262207 Iteration: 48|| Global Counts: [16, 35, 13]|| iter time: 0.12000513076782227 Iteration: 49|| Global Counts: [15, 43, 13]|| iter time: 0.11867403984069824 Iteration: 50|| Global Counts: [15, 42, 13]|| iter time: 0.13727807998657227 HDP-ALL Iteration: 1|| Global Counts: [10]|| iter time: 0.10990786552429199 Iteration: 2|| Global Counts: [10]|| iter time: 0.06658601760864258 Iteration: 3|| Global Counts: [10]|| iter time: 0.07351899147033691 Iteration: 4|| Global Counts: [10]|| iter time: 0.07680082321166992 Iteration: 5|| Global Counts: [10]|| iter time: 0.06832695007324219 Iteration: 6|| Global Counts: [10]|| iter time: 0.06442499160766602 Iteration: 7|| Global Counts: [10, 10]|| iter time: 0.08175086975097656 Iteration: 8|| Global Counts: [10, 10]|| iter time: 0.07950401306152344 Iteration: 9|| Global Counts: [10, 10]|| iter time: 0.07703399658203125 Iteration: 10|| Global Counts: [10, 10]|| iter time: 0.12406611442565918 Iteration: 11|| Global Counts: [10, 10]|| iter time: 0.08689188957214355 Iteration: 12|| Global Counts: [10, 10]|| iter time: 0.08514690399169922 Iteration: 13|| Global Counts: [10, 10]|| iter time: 0.17728590965270996 Iteration: 14|| Global Counts: [10, 10]|| iter time: 0.07640600204467773 Iteration: 15|| Global Counts: [10, 10]|| iter time: 0.08055686950683594 Iteration: 16|| Global Counts: [10, 10]|| iter time: 0.14979314804077148 Iteration: 17|| Global Counts: [10, 10]|| iter time: 0.07523989677429199 Iteration: 18|| Global Counts: [10, 10]|| iter time: 0.08143401145935059 Iteration: 19|| Global Counts: [10, 10]|| iter time: 0.08100509643554688 Iteration: 20|| Global Counts: [10, 10]|| iter time: 0.0758829116821289 Iteration: 21|| Global Counts: [10, 10, 10]|| iter time: 0.08707118034362793 Iteration: 22|| Global Counts: [7, 10, 13]|| iter time: 0.0937960147857666 Iteration: 23|| Global Counts: [7, 10, 13]|| iter time: 0.0900728702545166 Iteration: 24|| Global Counts: [7, 10, 13]|| iter time: 0.08991789817810059 Iteration: 25|| Global Counts: [7, 10, 12]|| iter time: 0.08977699279785156 Iteration: 26|| Global Counts: [7, 10, 10]|| iter time: 0.0902700424194336 Iteration: 27|| Global Counts: [7, 10, 11]|| iter time: 0.08615899085998535 Iteration: 28|| Global Counts: [7, 10, 10]|| iter time: 0.08729100227355957 Iteration: 29|| Global Counts: [7, 10, 10, 10]|| iter time: 0.0928499698638916 Iteration: 30|| Global Counts: [7, 10, 10, 11]|| iter time: 0.09835410118103027 Iteration: 31|| Global Counts: [7, 10, 7, 10]|| iter time: 0.09876298904418945 Iteration: 32|| Global Counts: [7, 10, 7, 11]|| iter time: 0.09951901435852051 Iteration: 33|| Global Counts: [7, 10, 7, 11]|| iter time: 0.09618592262268066 Iteration: 34|| Global Counts: [7, 10, 7, 11, 7]|| iter time: 0.10213088989257812 Iteration: 35|| Global Counts: [7, 10, 9, 9, 7]|| iter time: 0.16344404220581055 Iteration: 36|| Global Counts: [8, 10, 8, 8, 7]|| iter time: 0.10676693916320801 Iteration: 37|| Global Counts: [10, 10, 7, 9, 7]|| iter time: 0.10925793647766113 Iteration: 38|| Global Counts: [11, 10, 7, 10, 6]|| iter time: 0.10982704162597656 Iteration: 39|| Global Counts: [11, 10, 7, 13, 6]|| iter time: 0.11256909370422363 Iteration: 40|| Global Counts: [13, 10, 8, 11, 6]|| iter time: 0.1135859489440918 Iteration: 41|| Global Counts: [16, 10, 7, 8, 6]|| iter time: 0.10515999794006348 Iteration: 42|| Global Counts: [16, 10, 7, 7, 7, 16]|| iter time: 0.11358904838562012 Iteration: 43|| Global Counts: [5, 10, 7, 6, 7, 14]|| iter time: 0.13390207290649414 Iteration: 44|| Global Counts: [5, 10, 7, 6, 6, 15]|| iter time: 0.12098479270935059 Iteration: 45|| Global Counts: [5, 10, 7, 6, 6, 17]|| iter time: 0.11588287353515625 Iteration: 46|| Global Counts: [4, 10, 7, 6, 6, 17, 6]|| iter time: 0.12451004981994629 Iteration: 47|| Global Counts: [4, 10, 7, 6, 7, 19, 4]|| iter time: 0.13457703590393066 Iteration: 48|| Global Counts: [4, 10, 7, 6, 8, 19, 4]|| iter time: 0.12952804565429688 Iteration: 49|| Global Counts: [4, 10, 7, 6, 8, 19, 3, 19]|| iter time: 0.13306021690368652 Iteration: 50|| Global Counts: [7, 10, 7, 6, 8, 12, 4, 13]|| iter time: 0.15780901908874512 HDP-GLOBAL Iteration: 1|| Global Counts: [10]|| iter time: 0.09337091445922852 Iteration: 2|| Global Counts: [10]|| iter time: 0.06065201759338379 Iteration: 3|| Global Counts: [10]|| iter time: 0.06698393821716309 Iteration: 4|| Global Counts: [10]|| iter time: 0.06317400932312012 Iteration: 5|| Global Counts: [10]|| iter time: 0.0625150203704834 Iteration: 6|| Global Counts: [10]|| iter time: 0.06079292297363281 Iteration: 7|| Global Counts: [10, 10]|| iter time: 0.06635904312133789 Iteration: 8|| Global Counts: [10, 10]|| iter time: 0.07398009300231934 Iteration: 9|| Global Counts: [10, 10]|| iter time: 0.0743870735168457 Iteration: 10|| Global Counts: [10, 10]|| iter time: 0.07302999496459961 Iteration: 11|| Global Counts: [10, 10]|| iter time: 0.07143282890319824 Iteration: 12|| Global Counts: [10, 10]|| iter time: 0.07608485221862793 Iteration: 13|| Global Counts: [10, 10]|| iter time: 0.07465600967407227 Iteration: 14|| Global Counts: [10, 10, 10]|| iter time: 0.07155609130859375 Iteration: 15|| Global Counts: [7, 10, 13]|| iter time: 0.0855710506439209 Iteration: 16|| Global Counts: [8, 10, 11]|| iter time: 0.0858919620513916 Iteration: 17|| Global Counts: [8, 10, 10]|| iter time: 0.0815730094909668 Iteration: 18|| Global Counts: [8, 10, 10]|| iter time: 0.0815420150756836 Iteration: 19|| Global Counts: [7, 10, 10]|| iter time: 0.07758212089538574 Iteration: 20|| Global Counts: [7, 10, 10]|| iter time: 0.08308696746826172 Iteration: 21|| Global Counts: [7, 10, 10]|| iter time: 0.0809481143951416 Iteration: 22|| Global Counts: [7, 10, 10]|| iter time: 0.08330488204956055 Iteration: 23|| Global Counts: [7, 10, 10]|| iter time: 0.08144593238830566 Iteration: 24|| Global Counts: [7, 10, 10]|| iter time: 0.07847285270690918 Iteration: 25|| Global Counts: [8, 10, 10]|| iter time: 0.08363604545593262 Iteration: 26|| Global Counts: [7, 10, 10]|| iter time: 0.08128213882446289 Iteration: 27|| Global Counts: [8, 10, 10]|| iter time: 0.08153486251831055 Iteration: 28|| Global Counts: [8, 10, 10]|| iter time: 0.08348608016967773 Iteration: 29|| Global Counts: [8, 10, 10]|| iter time: 0.07883095741271973 Iteration: 30|| Global Counts: [8, 10, 10]|| iter time: 0.08311605453491211 Iteration: 31|| Global Counts: [8, 10, 10]|| iter time: 0.08098816871643066 Iteration: 32|| Global Counts: [8, 10, 10]|| iter time: 0.08668994903564453 Iteration: 33|| Global Counts: [8, 10, 10]|| iter time: 0.08283019065856934 Iteration: 34|| Global Counts: [7, 10, 10]|| iter time: 0.07932090759277344 Iteration: 35|| Global Counts: [7, 10, 10]|| iter time: 0.07929205894470215 Iteration: 36|| Global Counts: [8, 10, 10]|| iter time: 0.07870912551879883 Iteration: 37|| Global Counts: [7, 10, 10]|| iter time: 0.08058309555053711 Iteration: 38|| Global Counts: [8, 10, 10]|| iter time: 0.08019089698791504 Iteration: 39|| Global Counts: [7, 10, 10]|| iter time: 0.07875800132751465 Iteration: 40|| Global Counts: [7, 10, 10]|| iter time: 0.08307409286499023 Iteration: 41|| Global Counts: [7, 10, 10]|| iter time: 0.0786750316619873 Iteration: 42|| Global Counts: [7, 10, 10]|| iter time: 0.0801088809967041 Iteration: 43|| Global Counts: [8, 10, 10]|| iter time: 0.08195781707763672 Iteration: 44|| Global Counts: [8, 10, 10]|| iter time: 0.0781559944152832 Iteration: 45|| Global Counts: [7, 10, 10]|| iter time: 0.08321094512939453 Iteration: 46|| Global Counts: [8, 10, 10]|| iter time: 0.08067107200622559 Iteration: 47|| Global Counts: [8, 10, 10]|| iter time: 0.08173394203186035 Iteration: 48|| Global Counts: [7, 10, 10]|| iter time: 0.07969307899475098 Iteration: 49|| Global Counts: [8, 10, 10]|| iter time: 0.07702398300170898 Iteration: 50|| Global Counts: [9, 10, 10]|| iter time: 0.08392000198364258 DPMM-ALL DPMM-SEP vHDPMM-SEP Iteration: 1|| Global Counts: [1]|| iter time: 0.05018901824951172 Iteration: 2|| Global Counts: [1]|| iter time: 0.01036691665649414 Iteration: 3|| Global Counts: [1]|| iter time: 0.010900020599365234 Iteration: 4|| Global Counts: [1]|| iter time: 0.015118837356567383 Iteration: 5|| Global Counts: [1, 1]|| iter time: 0.011039018630981445 Iteration: 6|| Global Counts: [1, 1]|| iter time: 0.01214599609375 Iteration: 7|| Global Counts: [2, 1]|| iter time: 0.018700838088989258 Iteration: 8|| Global Counts: [2, 1]|| iter time: 0.014895915985107422 Iteration: 9|| Global Counts: [2, 1]|| iter time: 0.0165860652923584 Iteration: 10|| Global Counts: [2, 1]|| iter time: 0.021586894989013672 Iteration: 11|| Global Counts: [2, 1]|| iter time: 0.01681208610534668 Iteration: 12|| Global Counts: [2, 1]|| iter time: 0.013871908187866211 Iteration: 13|| Global Counts: [2, 1]|| iter time: 0.01708698272705078 Iteration: 14|| Global Counts: [3, 1]|| iter time: 0.015883207321166992 Iteration: 15|| Global Counts: [3, 1]|| iter time: 0.017752885818481445 Iteration: 16|| Global Counts: [3, 1]|| iter time: 0.014880895614624023 Iteration: 17|| Global Counts: [3, 1]|| iter time: 0.01745295524597168 Iteration: 18|| Global Counts: [3, 1]|| iter time: 0.014588117599487305 Iteration: 19|| Global Counts: [3, 1]|| iter time: 0.017714977264404297 Iteration: 20|| Global Counts: [3, 1]|| iter time: 0.01577901840209961 Iteration: 21|| Global Counts: [3, 1]|| iter time: 0.01785588264465332 Iteration: 22|| Global Counts: [3, 1]|| iter time: 0.014860153198242188 Iteration: 23|| Global Counts: [3, 1]|| iter time: 0.017524003982543945 Iteration: 24|| Global Counts: [3, 1]|| iter time: 0.014734029769897461 Iteration: 25|| Global Counts: [3, 1]|| iter time: 0.01739192008972168 Iteration: 26|| Global Counts: [3, 1]|| iter time: 0.01611614227294922 Iteration: 27|| Global Counts: [3, 1]|| iter time: 0.02287602424621582 Iteration: 28|| Global Counts: [3, 1]|| iter time: 0.014973878860473633 Iteration: 29|| Global Counts: [3, 1]|| iter time: 0.017306804656982422 Iteration: 30|| Global Counts: [3, 1]|| iter time: 0.0144500732421875 Iteration: 31|| Global Counts: [3, 1]|| iter time: 0.01770305633544922 Iteration: 32|| Global Counts: [3, 1]|| iter time: 0.016260862350463867 Iteration: 33|| Global Counts: [3, 1]|| iter time: 0.017709016799926758 Iteration: 34|| Global Counts: [3, 1]|| iter time: 0.01504206657409668 Iteration: 35|| Global Counts: [3, 1]|| iter time: 0.017616987228393555 Iteration: 36|| 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50|| Global Counts: [3, 1]|| iter time: 0.01940298080444336 Iteration: 1|| Global Counts: [1]|| iter time: 0.039520978927612305 Iteration: 2|| Global Counts: [1]|| iter time: 0.013664007186889648 Iteration: 3|| Global Counts: [1]|| iter time: 0.014520883560180664 Iteration: 4|| Global Counts: [1]|| iter time: 0.011398792266845703 Iteration: 5|| Global Counts: [1]|| iter time: 0.014280080795288086 Iteration: 6|| Global Counts: [1, 1]|| iter time: 0.011657953262329102 Iteration: 7|| Global Counts: [1, 1]|| iter time: 0.015439033508300781 Iteration: 8|| Global Counts: [1, 2]|| iter time: 0.013667106628417969 Iteration: 9|| Global Counts: [1, 2]|| iter time: 0.014284849166870117 Iteration: 10|| Global Counts: [2, 2]|| iter time: 0.018862009048461914 Iteration: 11|| Global Counts: [2, 2]|| iter time: 0.019922971725463867 Iteration: 12|| Global Counts: [2, 2]|| iter time: 0.017827987670898438 Iteration: 13|| Global Counts: [2, 2]|| iter time: 0.014526128768920898 Iteration: 14|| Global 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(Dict(7 => [7; 7; … ; 2; 2],4 => [3; 3; … ; 2; 2],9 => [1; 1; … ; 1; 1],10 => [1; 1; … ; 7; 1],2 => [1; 1; … ; 2; 2],3 => [4; 4; … ; 2; 2],5 => [4; 4; … ; 2; 2],8 => [2; 2; … ; 5; 5],6 => [2; 2; … ; 2; 2],1 => [1; 1; … ; 5; 5]…), Dict(7 => [3; 3; … ; 2; 2],4 => [1; 1; … ; 2; 2],9 => [3; 3; … ; 3; 3],10 => [3; 3; … ; 3; 3],2 => [3; 3; … ; 2; 2],3 => [1; 1; … ; 2; 2],5 => [1; 1; … ; 2; 2],8 => [2; 2; … ; 3; 3],6 => [2; 2; … ; 2; 2],1 => [3; 3; … ; 3; 3]…), [3, 3, 3, 3, 3, 3, 3, 3, 3, 3 … 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [[2, 2, 2, 2, 2, 2, 2, 2, 2, 2 … 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [2, 2, 2, 2, 2, 2, 2, 2, 2, 2 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2, 2, 2, 2 … 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3 … 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3 … 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1 … 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3 … 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]], Dict(7 => [1; 1; … ; 2; 2],4 => [3; 3; … ; 2; 2],9 => [1; 1; … ; 1; 1],10 => [1; 1; … ; 1; 1],2 => [1; 1; … ; 2; 2],3 => [3; 3; … ; 2; 2],5 => [3; 3; … ; 2; 2],8 => [2; 2; … ; 1; 1],6 => [2; 2; … ; 2; 2],1 => [1; 1; … ; 1; 1]…), Dict(7 => [1; 1; … ; 3; 3],4 => [3; 3; … ; 2; 2],9 => [1; 1; … ; 1; 1],10 => [1; 1; … ; 1; 1],2 => [1; 1; … ; 2; 2],3 => [2; 2; … ; 1; 1],5 => [4; 4; … ; 3; 3],8 => [1; 1; … ; 3; 3],6 => [2; 2; … ; 1; 1],1 => [5; 5; … ; 3; 3]…), Dict(7 => [2; 2; … ; 1; 1],4 => [1; 1; … ; 2; 2],9 => [2; 2; … ; 2; 2],10 => [2; 2; … ; 2; 2],2 => [1; 1; … ; 2; 2],3 => [2; 2; … ; 1; 1],5 => [2; 2; … ; 1; 1],8 => [3; 3; … ; 1; 1],6 => [1; 1; … ; 1; 1],1 => [1; 1; … ; 1; 1]…), Dict(7 => [2; 2; … ; 3; 3],4 => [3; 3; … ; 2; 2],9 => [1; 1; … ; 1; 1],10 => [3; 3; … ; 3; 3],2 => [4; 4; … ; 5; 5],3 => [5; 5; … ; 1; 4],5 => [6; 6; … ; 1; 1],8 => [4; 4; … ; 1; 1],6 => [4; 4; … ; 1; 1],1 => [1; 1; … ; 4; 4]…))
evaluate_all_results(labels_global,labels_local,hdp_all_global,hdp_global_global,dpmm_all_local,dpmm_seperated_local, vhdpmm_global, vhdpmm_local,vhdpmm_sep_global, vhdpmm_sep_local)
HDPMM NMI: 0.8247037529487768 HDPMM Global NMI: 0.9965057438935003 DPMM NMI: 0.07525700523292128 DPMM SEPERATED NMI: 0.7734244337920403 vHDPMM Global NMI: 0.9987526916835051 vHDPMM Local NMI: 0.8776641706369462 vHDPMM Sep Global NMI: 0.9989081132922045 vHDPMM Sep Local NMI: 0.8799099300832822
(0.8247037529487768, 0.9965057438935003, 0.07525700523292128, 0.7734244337920403, 0.9987526916835051, 0.8776641706369462, 0.9989081132922045, 0.8799099300832822)