How to use
E
method
in
weka.clusterers.EM

Best Java code snippets using weka.clusterers.EM.E (Showing top 4 results out of 315)

return E(inst, true);

 tll = E(cvTest, false);
} catch (Exception ex) {

 tll = E(cvTest, false);
} catch (Exception ex) {

return E(inst, true);

The E step of the EM algorithm. Estimate cluster membership probabilities.

<init>
Constructor.
setNumClusters
Set the number of clusters (-1 to select by CV).
CVClusters
estimate the number of clusters by cross validation on the training data.
EM_Init
Initialize the global aggregated estimators and storage.
EM_Report
verbose output for debugging
M
The M step of the EM algorithm.
M_reEstimate
buildClusterer
Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via opti
distributionForInstance
doEM
Perform the EM algorithm
estimate_priors
calculate prior probabilites for the clusters
getCapabilities
Returns default capabilities of the clusterer (i.e., the ones of SimpleKMeans).

Start an intent from android
scheduleAtFixedRate (ScheduledExecutorService)
notifyDataSetChanged (ArrayAdapter)
onCreateOptionsMenu (Activity)
VirtualMachine (com.sun.tools.attach)
A Java virtual machine. A VirtualMachine represents a Java virtual machine to which this Java vir
Thread (java.lang)
A thread is a thread of execution in a program. The Java Virtual Machine allows an application to ha
InetAddress (java.net)
An Internet Protocol (IP) address. This can be either an IPv4 address or an IPv6 address, and in pra
Permission (java.security)
Legacy security code; do not use.
ImageIO (javax.imageio)
Option (scala)
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