public class LogisticRegression extends StatModel
Modifier and Type | Field and Description |
---|---|
static int |
BATCH |
static int |
MINI_BATCH |
static int |
REG_DISABLE |
static int |
REG_L1 |
static int |
REG_L2 |
COMPRESSED_INPUT, PREPROCESSED_INPUT, RAW_OUTPUT, UPDATE_MODEL
Modifier and Type | Method and Description |
---|---|
static LogisticRegression |
create() |
Mat |
get_learnt_thetas() |
int |
getIterations() |
double |
getLearningRate() |
int |
getMiniBatchSize() |
int |
getRegularization() |
TermCriteria |
getTermCriteria() |
int |
getTrainMethod() |
float |
predict(Mat samples) |
float |
predict(Mat samples,
Mat results,
int flags) |
void |
setIterations(int val) |
void |
setLearningRate(double val) |
void |
setMiniBatchSize(int val) |
void |
setRegularization(int val) |
void |
setTermCriteria(TermCriteria val) |
void |
setTrainMethod(int val) |
empty, getVarCount, isClassifier, isTrained, train
clear, getDefaultName, save
public static final int BATCH
public static final int MINI_BATCH
public static final int REG_DISABLE
public static final int REG_L1
public static final int REG_L2
public static LogisticRegression create()
public Mat get_learnt_thetas()
public int getIterations()
public double getLearningRate()
public int getMiniBatchSize()
public int getRegularization()
public TermCriteria getTermCriteria()
public int getTrainMethod()
public void setIterations(int val)
public void setLearningRate(double val)
public void setMiniBatchSize(int val)
public void setRegularization(int val)
public void setTermCriteria(TermCriteria val)
public void setTrainMethod(int val)