Interface | Description |
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GLMMetrics |
Created by tomasnykodym on 1/5/16.
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Model.DeepFeatures | |
Model.ExemplarMembers | |
Model.GetMostImportantFeatures | |
Model.GLRMArchetypes | |
Model.LeafNodeAssignment | |
ModelParametersBuilderFactory<MP extends Model.Parameters> |
Factory for creating model parameters builders.
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ModelParametersBuilderFactory.ModelParametersBuilder<MP extends Model.Parameters> |
A generic interface to configure a given initial parameters object
via sequence of
ModelParametersBuilderFactory.ModelParametersBuilder.set(java.lang.String, java.lang.Object) method calls. |
ScoringInfo.HasEpochs | |
ScoringInfo.HasIterations | |
ScoringInfo.HasSamples | |
ToEigenVec |
Created by arno on 7/8/16.
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Class | Description |
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AUC2 |
One-pass approximate AUC
This algorithm can compute the AUC in 1-pass with good resolution.
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AUC2.AUCBuilder | |
ClusteringModel<M extends ClusteringModel<M,P,O>,P extends ClusteringModel.ClusteringParameters,O extends ClusteringModel.ClusteringOutput> |
Clustering Model
Generates a 2-D array of clusters.
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ClusteringModel.ClusteringOutput |
Output from all Clustering Models, includes generated clusters
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ClusteringModel.ClusteringParameters |
Clustering Model Parameters includes the number of clusters desired
|
ClusteringModelBuilder<M extends ClusteringModel<M,P,O>,P extends ClusteringModel.ClusteringParameters,O extends ClusteringModel.ClusteringOutput> | |
ConfusionMatrix | |
CreateFrame |
Create a Frame from scratch
If randomize = true, then the frame is filled with Random values.
|
Distribution |
Distribution functions to be used by ML Algos
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DMatrix |
Created by tomasnykodym on 11/13/14.
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DMatrix.MatrixMulStats |
Info about matrix multiplication currently in progress.
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DMatrix.MatrixMulTsk | |
DMatrix.TransposeTsk |
(MR)Task performing the matrix transpose.
|
FrameSplitter |
Frame splitter function to divide given frame into
multiple partitions based on given ratios.
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GainsLift | |
GainsLift.GainsLiftBuilder | |
Interaction |
Create new factors that represent interactions of the given factors
|
MeanResidualDeviance | |
MeanResidualDeviance.MeanResidualBuilder | |
Model<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> |
A Model models reality (hopefully).
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Model.GridSortBy | |
Model.InteractionPair |
This class represents a pair of interacting columns plus some additional data
about specific enums to be interacted when the vecs are categorical.
|
Model.Output |
Model-specific output class.
|
Model.Parameters |
Model-specific parameter class.
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ModelBuilder<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> |
Model builder parent class.
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ModelBuilder.ValidationMessage |
Can be an ERROR, meaning the parameters can't be used as-is,
a TRACE, which means the specified field should be hidden given
the values of other fields, or a WARN or INFO for informative
messages to the user.
|
ModelMetrics |
Container to hold the metric for a model as scored on a specific frame.
|
ModelMetrics.MetricBuilder<T extends ModelMetrics.MetricBuilder<T>> |
Class used to compute AUCs, CMs & HRs "on the fly" during other passes
over Big Data.
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ModelMetricsAutoEncoder | |
ModelMetricsAutoEncoder.MetricBuilderAutoEncoder | |
ModelMetricsBinomial | |
ModelMetricsBinomial.MetricBuilderBinomial<T extends ModelMetricsBinomial.MetricBuilderBinomial<T>> | |
ModelMetricsBinomialGLM | |
ModelMetricsBinomialGLM.ModelMetricsMultinomialGLM | |
ModelMetricsClustering | |
ModelMetricsClustering.MetricBuilderClustering | |
ModelMetricsMultinomial | |
ModelMetricsMultinomial.MetricBuilderMultinomial<T extends ModelMetricsMultinomial.MetricBuilderMultinomial<T>> | |
ModelMetricsRegression | |
ModelMetricsRegression.MetricBuilderRegression<T extends ModelMetricsRegression.MetricBuilderRegression<T>> | |
ModelMetricsRegressionGLM |
Created by tomasnykodym on 4/20/15.
|
ModelMetricsSupervised | |
ModelMetricsSupervised.MetricBuilderSupervised<T extends ModelMetricsSupervised.MetricBuilderSupervised<T>> | |
ModelMetricsUnsupervised | |
ModelMetricsUnsupervised.MetricBuilderUnsupervised<T extends ModelMetricsUnsupervised.MetricBuilderUnsupervised<T>> | |
ModelMojoWriter<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> |
Base class for serializing models into the MOJO format.
|
MultiModelMojoWriter<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> | |
PartialDependence |
Create a Frame from scratch
If randomize = true, then the frame is filled with Random values.
|
ScoreKeeper |
Low-weight keeper of scores
solely intended for display (either direct or as helper to create scoring history TwoDimTable).
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ScoringInfo |
Lightweight scoring history snapshot, for things like displaying the scoring history.
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SplitFrame |
Split given frame based on given ratio.
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SplitFrame.Frames | |
Transformer<T extends Keyed> |
Representation of transformation from type X to Y.
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VarImp |
Enum | Description |
---|---|
AUC2.ThresholdCriterion |
Criteria for 2-class Confusion Matrices
This is an Enum class, with an exec() function to compute the criteria
from the basic parts, and from an AUC2 at a given threshold index.
|
Model.Parameters.CategoricalEncodingScheme | |
Model.Parameters.FoldAssignmentScheme | |
ModelBuilder.BuilderVisibility |
Visibility for this algo: is it always visible, is it beta (always
visible but with a note in the UI) or is it experimental (hidden by
default, visible in the UI if the user gives an "experimental" flag at
startup); test-only builders are "experimental"
|
ScoreKeeper.StoppingMetric |