hex

Class Model.Parameters

java.lang.Object

water.Iced

hex.Model.Parameters

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, Freezable

Direct Known Subclasses:

ClusteringModel.ClusteringParameters, QuantileModel.QuantileParameters, SupervisedModel.SupervisedParameters

Enclosing class:

Model<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output>

public abstract static class Model.Parameters
extends Iced

Model-specific parameter class. Each model sub-class contains an instance of one of these containing its builder parameters, with model-specific parameters. E.g. KMeansModel extends Model and has a KMeansParameters extending Model.Parameters; sample parameters include K, whether or not to normalize, max iterations and the initial random seed.

The non-transient fields are input parameters to the model-building process, and are considered "first class citizens" by the front-end - the front-end will cache Parameters (in the browser, in JavaScript, on disk) and rebuild Parameter instances from those caches.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
boolean	_ignore_const_cols
java.lang.String[]	_ignored_columns
Key<Frame>	_model_id
boolean	_score_each_iteration
Key<Frame>	_train
Key<Frame>	_valid

Constructor Summary

Constructors

Constructor and Description
Model.Parameters()

Method Summary

Methods

Modifier and Type	Method and Description
protected long	checksum_impl() Compute a checksum based on all non-transient non-static ice-able assignable fields (incl.
protected boolean	defaultDropConsCols()
protected boolean	defaultDropNA20Cols()
double	missingColumnsType() Type of missing columns during adaptation between train/test datasets Overload this method for models that have sparse data handling - a zero will preserve the sparseness.
void	read_lock_frames(Job job) Read-Lock both training and validation User frames.
void	read_unlock_frames(Job job) Read-UnLock both training and validation User frames.
Frame	train()
Frame	valid()

Methods inherited from class water.Iced

clone, frozenType, read_impl, read, readExternal, readJSON_impl, readJSON, toJsonString, write_impl, write, writeExternal, writeHTML_impl, writeHTML, writeJSON_impl, writeJSON

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

_model_id

public Key<Frame> _model_id

_train

public Key<Frame> _train

_valid

public Key<Frame> _valid

_ignored_columns

public java.lang.String[] _ignored_columns

_ignore_const_cols

public boolean _ignore_const_cols

_score_each_iteration

public boolean _score_each_iteration

Constructor Detail

Model.Parameters

public Model.Parameters()

Method Detail

train

public final Frame train()

Returns:

the training frame instance

valid

public final Frame valid()

Returns:

the validation frame instance, or null if a validation frame was not specified

read_lock_frames

public void read_lock_frames(Job job)

Read-Lock both training and validation User frames.

read_unlock_frames

public void read_unlock_frames(Job job)

Read-UnLock both training and validation User frames.

defaultDropNA20Cols

protected boolean defaultDropNA20Cols()

defaultDropConsCols

protected boolean defaultDropConsCols()

missingColumnsType

public double missingColumnsType()

Type of missing columns during adaptation between train/test datasets Overload this method for models that have sparse data handling - a zero will preserve the sparseness. Otherwise, NaN is used.

Returns:

real-valued number (can be NaN)

checksum_impl

protected long checksum_impl()

Compute a checksum based on all non-transient non-static ice-able assignable fields (incl. inherited ones) which have @API annotations. Sort the fields first, since reflection gives us the fields in random order and we don't want the checksum to be affected by the field order. NOTE: if a field is added to a Parameters class the checksum will differ even when all the previous parameters have the same value. If a client wants backward compatibility they will need to compare parameter values explicitly.

Returns:

checksum