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Mélanges de GLMs et nombre de composantes : application ... - Scor

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C.6. Famille <strong>de</strong> produits Pure Savings<br />

Figure C.29 – Importance <strong>de</strong>s variables explicatives, produit Pure Savings.<br />

Variable importance for Pure_savings (All) on<br />

3 months basis<br />

General and by class error rate of Pure_savings (All) in<br />

3 months basis<br />

duration<br />

lapse.age<br />

saving.premium<br />

un<strong>de</strong>rwriting.age<br />

face.amount<br />

duration.range<br />

savingPrem.range<br />

risk.premium<br />

premium.frequency<br />

un<strong>de</strong>rwritingAge.range<br />

fa.range<br />

dist.channel<br />

gen<strong>de</strong>r<br />

Error<br />

0.10 0.12 0.14 0.16 0.18<br />

0 500 1000 1500 2000 2500<br />

MeanDecreaseGini<br />

0 10 20 30 40<br />

trees<br />

C.6.3<br />

Boxplot <strong>de</strong>s coefficients du modèle<br />

Comp. 2<br />

−1.5 −1.0 −0.5 0.0 0.5 1.0<br />

Comp. 3<br />

Comp. 4<br />

(Intercept)<br />

−1.5 −1.0 −0.5 0.0 0.5 1.0<br />

−1.5 −1.0 −0.5 0.0 0.5 1.0<br />

Figure C.30 – Coefficients <strong>de</strong> régression estimés <strong>de</strong>s poids <strong>de</strong>s <strong>composantes</strong>, Pure Savings.<br />

219

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