Algorithme de classification Newton Raphson (régression logistique)

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)
 
}

Definit d'abord ta fonction

Commence dájà par définir ta fonction maxNR.

max NR est une fonction dans le package maxLik

C'est quoi les partitions don tut parles?

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