Modifier and Type | Class and Description |
---|---|
static class |
ConfusionMatrix.ErrMetric |
Modifier and Type | Field and Description |
---|---|
long[][] |
_arr |
double[] |
_classErr |
double |
_predErr |
static DocGen.FieldDoc[] |
DOC_FIELDS |
Constructor and Description |
---|
ConfusionMatrix(int n) |
ConfusionMatrix(long[][] value) |
ConfusionMatrix(long[][] value,
int dim) |
Modifier and Type | Method and Description |
---|---|
double |
accuracy()
The percentage of predictions that are correct.
|
void |
add(ConfusionMatrix other) |
void |
add(int i,
int j) |
double[] |
classErr() |
double |
classErr(int c) |
long |
classErrCount(int c) |
ConfusionMatrix |
clone() |
double |
err() |
long |
errCount() |
double |
F0point5()
Returns the F-measure which combines precision and recall and weights precision higher than recall.
|
double |
F1()
Returns the F-measure which combines precision and recall in a balanced way.
|
double |
F2()
Returns the F-measure which combines precision and recall and weights recall higher than precision.
|
boolean |
isBinary() |
double |
max_per_class_error()
The maximum per-class error
|
double |
mcc()
The Matthews Correlation Coefficient, takes true negatives into account in contrast to F-Score
See MCC
MCC = Correlation between observed and predicted binary classification
|
int |
nclasses() |
double |
precision()
The percentage of positive predictions that are correct.
|
double |
recall()
The percentage of positive labeled instances that were predicted as positive.
|
void |
reComputeErrors() |
int |
size() |
double |
specificity()
The percentage of negative labeled instances that were predicted as negative.
|
void |
toHTML(java.lang.StringBuilder sb,
java.lang.String[] domain) |
com.google.gson.JsonArray |
toJson() |
java.lang.String |
toString() |
long |
totalRows() |
frozenType, init, newInstance, read, toDocField, write, writeJSON, writeJSONFields
public static DocGen.FieldDoc[] DOC_FIELDS
@Request.API(help="Confusion matrix (Actual/Predicted)") public long[][] _arr
@Request.API(help="Prediction error by class") public final double[] _classErr
@Request.API(help="Prediction error") public double _predErr
public ConfusionMatrix(int n)
public ConfusionMatrix(long[][] value)
public ConfusionMatrix(long[][] value, int dim)
public ConfusionMatrix clone()
public void add(int i, int j)
public double[] classErr()
public final int size()
public void reComputeErrors()
public final long classErrCount(int c)
public final double classErr(int c)
public long totalRows()
public void add(ConfusionMatrix other)
public double err()
public long errCount()
public double accuracy()
public double specificity()
public double recall()
public double precision()
public double mcc()
public double max_per_class_error()
public final int nclasses()
public final boolean isBinary()
public double F1()
public double F2()
public double F0point5()
public java.lang.String toString()
toString
in class java.lang.Object
public com.google.gson.JsonArray toJson()
public void toHTML(java.lang.StringBuilder sb, java.lang.String[] domain)