Hi,
using E-M algorithm it is possible to divide dataset into K fuzzy
clusters. K is predefined input variable. I'm wondering how to detect
best-fitting K? Should I run fuzzy cluster many times, and choose
most probable K, or is there a better way?
--
Regards
Mariusz
#includestdio.h
struct key {
int min;
double sum;
};
int main(int argc,char **argv)
{
int n,i,j,k;
int start=0,end=0;
double currentValue=0,eValue=0;
struct key opt[10];
int a[10];
while ( scanf(%d,n) != EOF )
{
This idea sems to be fastest what u can do ..as i know.
Then u need to have 2 booleans.
CanItBeLocked: true/false
ActualStatus: locked/unlocked.
So whenever you want to query a node u simply check CanItBeLocked.
But when u actually want to lock/unlock it. then you need to do a
status
