| Interface | Description |
|---|---|
| GLMMetrics |
Created by tomasnykodym on 1/5/16.
|
| Model.DeepFeatures | |
| Model.ExemplarMembers | |
| Model.GLRMArchetypes | |
| Model.LeafNodeAssignment | |
| ModelParametersBuilderFactory<MP extends Model.Parameters> |
Factory for creating model parameters builders.
|
| 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.
|
| Class | Description |
|---|---|
| AUC2 |
One-pass approximate AUC
This algorithm can compute the AUC in 1-pass with good resolution.
|
| 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.
|
| ClusteringModel.ClusteringOutput |
Output from all Clustering Models, includes generated clusters
|
| 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
|
| DMatrix |
Created by tomasnykodym on 11/13/14.
|
| DMatrix.MatrixMulStats |
Info about matrix multiplication currently in progress.
|
| 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.
|
| 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).
|
| 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.
|
| ModelBuilder<M extends Model<M,P,O>,P extends Model.Parameters,O extends Model.Output> |
Model builder parent class.
|
| 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.
|
| 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 | |
| ScoreKeeper |
Low-weight keeper of scores
solely intended for display (either direct or as helper to create scoring history TwoDimTable).
|
| ScoringInfo |
Lightweight scoring history snapshot, for things like displaying the scoring history.
|
| SplitFrame |
Split given frame based on given ratio.
|
| SplitFrame.Frames | |
| Transformer<T extends Keyed> |
Representation of transformation from type X to Y.
|
| 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.
|
| Distribution.Family | |
| 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 |