In [1]:

    

using StatsBase

s = [874, 1293, 1070] ./ 3237
p = [224, 242, 236] ./ 702

s = WeightVec(s)
p = WeightVec(p)


    

    
Out[1]:





StatsBase.WeightVec{Float64,Array{Float64,1}}([0.319088,0.344729,0.336182],1.0)

In [4]:

    

model = "cnn beam"

rs_1 = [0.6430205949656751, 0.7078825347758887, 0.6785046728971963];
rp_1 = [0.2631578947368421, 0.20161290322580644, 0.2831858407079646];

rs_2 = [0.6498855835240275, 0.7136222910216719, 0.6635514018691588];
rp_2 = [0.22522522522522523, 0.2605042016806723, 0.2845528455284553];

rs_3 = [0.6224256292906178, 0.7357032457496137, 0.6710280373831776];
rp_3 = [0.21929824561403508, 0.2661290322580645, 0.24778761061946902];

rs_4 = [0.6498855835240275, 0.7368421052631579, 0.6560747663551402];
rp_4 = [0.26126126126126126, 0.29411764705882354, 0.2845528455284553];

rs_5 = [0.6590389016018307, 0.6893353941267388, 0.6485981308411215];
rp_5 = [0.2894736842105263, 0.18548387096774194, 0.18584070796460178];

rs_6 = [0.6750572082379863, 0.7043343653250774, 0.6897196261682244];
rp_6 = [0.2972972972972973, 0.24369747899159663, 0.3089430894308943];

rs_ens_1 = [0.665903890160183, 0.7202472952086554, 0.7009345794392523];
rp_ens_1 = [0.2807017543859649, 0.2661290322580645, 0.3185840707964602];

rs_ens_2 = [0.6956521739130435, 0.7430340557275542, 0.6841121495327103];
rp_ens_2 = [0.27927927927927926, 0.3025210084033613, 0.3333333333333333];

rs_m = (rs_1 + rs_2 + rs_3 + rs_4 + rs_5 + rs_6) / 6
rp_m = (rp_1 + rp_2 + rp_3 + rp_4 + rp_5 + rp_6) / 6

rs_ens_m = (rs_ens_1 + rs_ens_2) / 2
rp_ens_m = (rp_ens_1 + rp_ens_2) / 2

println("Single: $(rs_m)")
println("Paragraph: $(rp_m)")
println("Weighted Single: $(mean_and_std(rs_m, s))")
println("Weighted Paragraph: $(mean_and_std(rp_m, p))")
println("Ensemble Weighted Single: $(mean_and_std(rs_ens_m, s))")
println("Ensemble Weighted Paragraph: $(mean_and_std(rp_ens_m, p))")


    

    




Single: [0.649886,0.71462,0.667913]
Paragraph: [0.259286,0.241924,0.26581]
Weighted Single: (0.6817022900621439,0.02773097953287085)
Weighted Paragraph: (0.25549416536789626,0.010190463535823686)
Ensemble Weighted Single: (0.7049772608527215,0.02221177357059797)
Ensemble Weighted Paragraph: (0.29693843928469443,0.020727345318575174)

In [3]:

    

rs_ens10_1 = [];
rp_ens10_1 = [];

rs_ens10_2 = [];
rp_ens10_2 = [];

rs_ens_m = (rs_ens10_1 + rs_ens10_2) / 2
rp_ens_m = (rp_ens10_1 + rp_ens10_2) / 2

println("Ensemble10 Weighted Single: $(mean_and_std(rs_ens_m, s))")
println("Ensemble10 Weighted Paragraph: $(mean_and_std(rp_ens_m, p))")


    

    




Ensemble10 Weighted Single: (0.7241341459653547,0.019874746288752722)
Ensemble10 Weighted Paragraph: (0.2911213294598043,0.03758720426255375)

In [ ]: