| biz.sc.mm.dm |
This package contains basic infrastructure for all other Górnik MM objects.
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| biz.sc.mm.dm.algorithm.abm |
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| biz.sc.mm.dm.algorithm.bivariate |
Algorithms settings for bivariate models.
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| biz.sc.mm.dm.algorithm.deduplication |
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| biz.sc.mm.dm.algorithm.deduplication.customcode |
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| biz.sc.mm.dm.algorithm.deduplication.metrics |
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| biz.sc.mm.dm.algorithm.discriminant |
Binary Linear Discriminant Analysis algorithm settings and model.
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| biz.sc.mm.dm.algorithm.ensembles |
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| biz.sc.mm.dm.algorithm.ets |
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| biz.sc.mm.dm.algorithm.featureselection |
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| biz.sc.mm.dm.algorithm.feedforwardneuralnet |
Settings and algorithms for feedforward neural networks.
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| biz.sc.mm.dm.algorithm.gam |
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| biz.sc.mm.dm.algorithm.gwaselection |
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| biz.sc.mm.dm.algorithm.kmean |
KMeans Clustering algorithm settings and model
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| biz.sc.mm.dm.algorithm.kohonen |
Settings and algorithms for Kohonen neural networks.
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| biz.sc.mm.dm.algorithm.likelihood.data |
Likelihood-based models common data interface.
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| biz.sc.mm.dm.algorithm.likelihood.optimization |
Common interface for nonlinear optimization methods.
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| biz.sc.mm.dm.algorithm.mars |
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| biz.sc.mm.dm.algorithm.mcmc |
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| biz.sc.mm.dm.algorithm.mcmc.logistic |
MCMC Logistic regression algorithm settings.
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| biz.sc.mm.dm.algorithm.naivebayes |
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| biz.sc.mm.dm.algorithm.regression |
Common classes for regression models.
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| biz.sc.mm.dm.algorithm.regression.irls |
IRLS regression algorithm settings.
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| biz.sc.mm.dm.algorithm.regression.linear |
Linear regression algorithm settings, model and model statistics.
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| biz.sc.mm.dm.algorithm.regression.logistic |
Logistic regression algorithm settings and model.
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| biz.sc.mm.dm.algorithm.regression.weighted |
Weighted regression model statistics.
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| biz.sc.mm.dm.algorithm.regularizedregression |
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| biz.sc.mm.dm.algorithm.socialnets |
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| biz.sc.mm.dm.algorithm.socialnets.alg |
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| biz.sc.mm.dm.algorithm.socialnets.prop |
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| biz.sc.mm.dm.algorithm.socialnets.visual |
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| biz.sc.mm.dm.algorithm.survival.cox |
Cox algorithm settings.
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| biz.sc.mm.dm.algorithm.survival.nonparametric |
Nonparametric survival algorithm settings.
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| biz.sc.mm.dm.algorithm.survival.util |
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| biz.sc.mm.dm.algorithm.timeseries |
Common settings for TimeSeries algorithms.
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| biz.sc.mm.dm.algorithm.timeseries.arch |
ARCH algorithm settings.
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| biz.sc.mm.dm.algorithm.timeseries.garch |
GARCH algorithm settings.
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| biz.sc.mm.dm.algorithm.tree |
Algorithm settings for classification trees.
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| biz.sc.mm.dm.algorithm.tree.classification |
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| biz.sc.mm.dm.algorithm.tree.nulls |
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| biz.sc.mm.dm.algorithm.tree.regression |
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| biz.sc.mm.dm.algorithm.weka |
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| biz.sc.mm.dm.base |
This package contains base interfaces for Górnik MM.
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| biz.sc.mm.dm.clustering |
This package contains infrastructure for clustering models.
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| biz.sc.mm.dm.data |
This package contains interfaces for data representation.
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| biz.sc.mm.dm.modelstats.discriminant |
Linear Discriminant Analysis model statistics.
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| biz.sc.mm.dm.modelstats.ets |
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| biz.sc.mm.dm.modelstats.feedforwardneuralnet |
Model statistics for feedforward neural networks.
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| biz.sc.mm.dm.modelstats.gam |
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| biz.sc.mm.dm.modelstats.kmean |
KMeans clustering model statistics.
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| biz.sc.mm.dm.modelstats.kohonen |
Model statistics for Kohonen neural networks.
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| biz.sc.mm.dm.modelstats.mars |
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| biz.sc.mm.dm.modelstats.mcmc |
MCMC model statistics.
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| biz.sc.mm.dm.modelstats.mcmc.logistic |
Common model statistics for MCMC regression models.
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| biz.sc.mm.dm.modelstats.naivebayes |
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| biz.sc.mm.dm.modelstats.regularizedregression |
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| biz.sc.mm.dm.modelstats.statistical |
Common model statistics for statistical models.
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| biz.sc.mm.dm.modelstats.statistical.bivariate |
Model statistics for bivariate models.
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| biz.sc.mm.dm.modelstats.statistical.regression |
Common model statistics for all regression models.
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| biz.sc.mm.dm.modelstats.statistical.regression.linear |
Common model statistics for all linear regression models.
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| biz.sc.mm.dm.modelstats.statistical.regression.logistic |
Common model statistics for all logistic regression models.
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| biz.sc.mm.dm.modelstats.survival |
Survival model statistics.
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| biz.sc.mm.dm.modelstats.timeseries |
Time Series model statistics.
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| biz.sc.mm.dm.modelstats.tree |
Model details for classification trees.
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| biz.sc.mm.dm.modelstats.tree.classification |
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| biz.sc.mm.dm.modelstats.tree.regression |
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| biz.sc.mm.dm.scoringcard |
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| biz.sc.mm.dm.scoringcode |
Provides ability to generate scoring code for various mining models.
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| biz.sc.mm.dm.statistics |
This package contains classes and interfaces regarding statistics.
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| biz.sc.mm.dm.supervised |
This package contains infrastructure for supervised models.
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| biz.sc.mm.dm.supervised.approximation |
This package contains infrastructure for aproximation models.
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| biz.sc.mm.dm.supervised.classification |
This package contains infrastructure for classification models.
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| biz.sc.mm.dm.supervised.classification.bivariate |
Bivariate function settings and usage options.
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| biz.sc.mm.dm.supervised.ets |
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| biz.sc.mm.dm.supervised.statistical |
Common settings for statistical models, including nonlinear optimization settings and variable selection settings.
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| biz.sc.mm.dm.supervised.statistical.classification |
Common interfaces and options for all likelihood-based classification models.
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| biz.sc.mm.dm.supervised.statistical.classification.bivariate |
Common interfaces and options for all bivariate classification models.
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| biz.sc.mm.dm.supervised.statistical.survival |
Common interfaces and options for all survival models.
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| biz.sc.mm.dm.supervised.statistical.timeseries |
Common interfaces and options for all timeseries models.
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| biz.sc.mm.dm.supervised.survival |
Survival function settings, apply task and test task.
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| biz.sc.mm.dm.supervised.timeseries |
TimeSeries function settings, apply task and test task.
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| biz.sc.mm.dm.task |
This package contains infrastructure for representing tasks.
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| biz.sc.mm.transformation |
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| biz.sc.mm.transformation.parameters |
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| biz.sc.mm.transformation.settings |
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| biz.sc.util |
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