hex
Class KMeans2.KMeans2Model
java.lang.Object
water.Iced
water.Model
hex.KMeans2.KMeans2Model
- All Implemented Interfaces:
- java.lang.Cloneable, Freezable, Job.Progress
- Enclosing class:
- KMeans2
public static class KMeans2.KMeans2Model
- extends Model
- implements Job.Progress
| Nested classes/interfaces inherited from class water.Model |
Model.SB |
|
Method Summary |
float |
progress()
|
protected float[] |
score0(Chunk[] chunks,
int rowInChunk,
double[] tmp,
float[] preds)
Bulk scoring API for one row. |
protected float[] |
score0(double[] data,
float[] preds)
Subclasses implement the scoring logic. |
| Methods inherited from class water.Model |
adapt, adapt, classNames, cm, delete, getDomainMapping, isClassifier, nclasses, responseName, score, score, score, score, score, testJavaScoring, toJava, toJavaInit, toJavaInit, toJavaPredictBody, varimp |
| Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
DOC_FIELDS
public static DocGen.FieldDoc[] DOC_FIELDS
clusters
public double[][] clusters
error
public double error
normalized
public boolean normalized
max_iter
public int max_iter
iterations
public int iterations
cluster_variances
public double[] cluster_variances
KMeans2.KMeans2Model
public KMeans2.KMeans2Model(Key selfKey,
Key dataKey,
java.lang.String[] names,
java.lang.String[][] domains)
progress
public float progress()
- Specified by:
progress in interface Job.Progress
score0
protected float[] score0(Chunk[] chunks,
int rowInChunk,
double[] tmp,
float[] preds)
- Description copied from class:
Model
- Bulk scoring API for one row. Chunks are all compatible with the model,
and expect the last Chunks are for the final distribution & prediction.
Default method is to just load the data into the tmp array, then call
subclass scoring logic.
- Overrides:
score0 in class Model
score0
protected float[] score0(double[] data,
float[] preds)
- Description copied from class:
Model
- Subclasses implement the scoring logic. The data is pre-loaded into a
re-used temp array, in the order the model expects. The predictions are
loaded into the re-used temp array, which is also returned.
- Specified by:
score0 in class Model