Discussion :

[lapetitechercheuse]

Je suis débutante et j'ai besoin de votre aide. Je veux appliquer la methode de Newton Raphson à la classification. j'ai fait ce petit algorithme mais je ne sais pa comment extraire les classes ( les partitions).

Code :

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mat= matrix (c (1,5,10,6,7,4,5,3,9,12,5,6,8,15,4,2,3,4,18,7,5,7,8,5,9,2,3,6,2,9,3,6,9,19,4), ncol=5,nrow=7)
data=cbind(1,mat)
n=dim(data)[1]
m=dim(data)[2]
beta<-seq(from=1,to=0.1,length=m)
logll <- function(x , beta=c()) 
{
  beta<-c(1,0.8,0.6,0.4,0.2,0.1)
  z<-x %*% beta
  p<-1/(1+exp(-z))
  if (p<0.5) 
    y<-0
  if (p>0.5) 
    y<-1
  logll<-sum((y*log(p)+(1-y)*log(1-p)))
}
 
for (i in 1:n)
{
  x<-matrix(data[i,],ncol=m,nrow=1)
  b = maxNR(logll, start=beta, print.level=2)
  summary(b)
 
}

[Americano]

Commence dájà par définir ta fonction maxNR.

[lapetitechercheuse]

max NR est une fonction dans le package maxLik

[Americano]

Voilà ce que donne ton modèle. Tu appeles quoi les partitions?

Code :

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----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12 
----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12 
----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12 
----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12 
----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12 
----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12 
----- Initial parameters: -----
fcn value: -0.09646085 
     parameter initial gradient free
[1,]      1.00      0.091954550    1
[2,]      0.82      0.073563640    1
[3,]      0.64      0.055172730    1
[4,]      0.46      0.036781820    1
[5,]      0.28      0.018390910    1
[6,]      0.10      0.009195455    1
Condition number of the (active) hessian: 7652.405 
-----Iteration 1 -----
-----Iteration 2 -----
-----Iteration 3 -----
--------------
gradient close to zero 
3  iterations
estimate: -77.09056 54.092 -49.81695 81.35279 146.798 272.3115 
Function value: -9.081846e-12