public class EM extends StatModel
Modifier and Type | Field and Description |
---|---|
static int |
COV_MAT_DEFAULT |
static int |
COV_MAT_DIAGONAL |
static int |
COV_MAT_GENERIC |
static int |
COV_MAT_SPHERICAL |
static int |
DEFAULT_MAX_ITERS |
static int |
DEFAULT_NCLUSTERS |
static int |
START_AUTO_STEP |
static int |
START_E_STEP |
static int |
START_M_STEP |
COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL
Modifier and Type | Method and Description |
---|---|
static EM |
__fromPtr__(long addr) |
static EM |
create() |
int |
getClustersNumber() |
int |
getCovarianceMatrixType() |
void |
getCovs(java.util.List<Mat> covs) |
Mat |
getMeans() |
TermCriteria |
getTermCriteria() |
Mat |
getWeights() |
static EM |
load(java.lang.String filepath) |
static EM |
load(java.lang.String filepath,
java.lang.String nodeName) |
float |
predict(Mat samples) |
float |
predict(Mat samples,
Mat results) |
float |
predict(Mat samples,
Mat results,
int flags) |
double[] |
predict2(Mat sample,
Mat probs) |
void |
setClustersNumber(int val) |
void |
setCovarianceMatrixType(int val) |
void |
setTermCriteria(TermCriteria val) |
boolean |
trainE(Mat samples,
Mat means0) |
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0) |
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0) |
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0,
Mat logLikelihoods) |
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0,
Mat logLikelihoods,
Mat labels) |
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0,
Mat logLikelihoods,
Mat labels,
Mat probs) |
boolean |
trainEM(Mat samples) |
boolean |
trainEM(Mat samples,
Mat logLikelihoods) |
boolean |
trainEM(Mat samples,
Mat logLikelihoods,
Mat labels) |
boolean |
trainEM(Mat samples,
Mat logLikelihoods,
Mat labels,
Mat probs) |
boolean |
trainM(Mat samples,
Mat probs0) |
boolean |
trainM(Mat samples,
Mat probs0,
Mat logLikelihoods) |
boolean |
trainM(Mat samples,
Mat probs0,
Mat logLikelihoods,
Mat labels) |
boolean |
trainM(Mat samples,
Mat probs0,
Mat logLikelihoods,
Mat labels,
Mat probs) |
calcError, empty, getVarCount, isClassifier, isTrained, train, train, train
clear, getDefaultName, getNativeObjAddr, save
public static final int COV_MAT_DEFAULT
public static final int COV_MAT_DIAGONAL
public static final int COV_MAT_GENERIC
public static final int COV_MAT_SPHERICAL
public static final int DEFAULT_MAX_ITERS
public static final int DEFAULT_NCLUSTERS
public static final int START_AUTO_STEP
public static final int START_E_STEP
public static final int START_M_STEP
public static EM __fromPtr__(long addr)
public static EM create()
public int getClustersNumber()
public int getCovarianceMatrixType()
public void getCovs(java.util.List<Mat> covs)
public Mat getMeans()
public TermCriteria getTermCriteria()
public Mat getWeights()
public static EM load(java.lang.String filepath)
public static EM load(java.lang.String filepath, java.lang.String nodeName)
public void setClustersNumber(int val)
public void setCovarianceMatrixType(int val)
public void setTermCriteria(TermCriteria val)
public boolean trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods, Mat labels)
public boolean trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods, Mat labels, Mat probs)
public boolean trainEM(Mat samples)