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Package ML
source code
module containing machine learning code
Submodules
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rdkit.ML.AnalyzeComposite
:
command line utility to report on the contributions of descriptors to tree-based composite models
rdkit.ML.BuildComposite
:
command line utility for building composite models
rdkit.ML.Cluster
rdkit.ML.Cluster.Butina
:
Implementation of the clustering algorithm published in:...
rdkit.ML.Cluster.ClusterUtils
:
utility functions for clustering
rdkit.ML.Cluster.ClusterVis
:
Cluster tree visualization using Sping
rdkit.ML.Cluster.Clusters
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contains the Cluster class for representing hierarchical cluster trees
rdkit.ML.Cluster.Murtagh
:
Interface to the C++ Murtagh hierarchic clustering code
rdkit.ML.Cluster.Resemblance
:
code for dealing with resemblance (metric) matrices
rdkit.ML.Cluster.Standardize
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contains code for standardization of data matrices for clustering
rdkit.ML.Composite
rdkit.ML.Composite.AdjustComposite
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functionality to allow adjusting composite model contents
rdkit.ML.Composite.BayesComposite
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code for dealing with Bayesian composite models
rdkit.ML.Composite.Composite
:
code for dealing with composite models
rdkit.ML.CompositeRun
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contains a class to store parameters for and results from...
rdkit.ML.Data
rdkit.ML.Data.DataUtils
:
Utilities for data manipulation
rdkit.ML.Data.FindQuantBounds
rdkit.ML.Data.MLData
:
classes to be used to help work with data sets
rdkit.ML.Data.Quantize
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Automatic search for quantization bounds
rdkit.ML.Data.SplitData
rdkit.ML.Data.Stats
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various statistical operations on data
rdkit.ML.Data.Transforms
rdkit.ML.DecTree
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Here we're implementing the Decision Tree stuff found in Chapter 3 of Tom Mitchell's Machine Learning Book.
rdkit.ML.DecTree.BuildQuantTree
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rdkit.ML.DecTree.BuildSigTree
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rdkit.ML.DecTree.CrossValidate
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handles doing cross validation with decision trees
rdkit.ML.DecTree.DecTree
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Defines the class _DecTreeNode_, used to represent decision trees
rdkit.ML.DecTree.Forest
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code for dealing with forests (collections) of decision trees
rdkit.ML.DecTree.ID3
:
ID3 Decision Trees
rdkit.ML.DecTree.PruneTree
:
Contains functionality for doing tree pruning
rdkit.ML.DecTree.QuantTree
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Defines the class _QuantTreeNode_, used to represent decision trees with automatic quantization bounds
rdkit.ML.DecTree.SigTree
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Defines the class SigTreeNode, used to represent trees that use signatures (bit vectors) to represent data.
rdkit.ML.DecTree.Tree
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Implements a class used to represent N-ary trees
rdkit.ML.DecTree.TreeUtils
:
Utilities for working with trees
rdkit.ML.DecTree.TreeVis
:
functionality for drawing trees on sping canvases
rdkit.ML.Descriptors
rdkit.ML.Descriptors.CompoundDescriptors
:
descriptor calculator for compounds defined by a composition alone...
rdkit.ML.Descriptors.Descriptors
:
Various bits and pieces for calculating descriptors
rdkit.ML.Descriptors.MoleculeDescriptors
:
Various bits and pieces for calculating Molecular descriptors
rdkit.ML.Descriptors.Parser
:
The "parser" for compound descriptors.
rdkit.ML.EnrichPlot
:
Command line tool to construct an enrichment plot from saved composite models
rdkit.ML.GrowComposite
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command line utility for growing composite models
rdkit.ML.InfoTheory
:
Information Theory functionality
rdkit.ML.InfoTheory.BitClusterer
rdkit.ML.InfoTheory.BitRank
:
Functionality for ranking bits using info gains
rdkit.ML.InfoTheory.entropy
:
Informational Entropy functions
rdkit.ML.KNN
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rdkit.ML.KNN.CrossValidate
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handles doing cross validation with k-nearest neighbors model
rdkit.ML.KNN.DistFunctions
rdkit.ML.KNN.KNNClassificationModel
:
Define the class _KNNClassificationModel_, used to represent a k-nearest neighbhors classification model
rdkit.ML.KNN.KNNModel
:
Define the class _KNNModel_, used to represent a k-nearest neighbhors model
rdkit.ML.KNN.KNNRegressionModel
:
Define the class _KNNRegressionModel_, used to represent a k-nearest neighbhors regression model
rdkit.ML.MLUtils
rdkit.ML.MLUtils.VoteImg
:
functionality for generating an image showing the results of a composite model voting on a data set
rdkit.ML.MatOps
:
Matrix operations which may or may not come in handy some day
rdkit.ML.ModelPackage
rdkit.ML.ModelPackage.PackageUtils
rdkit.ML.ModelPackage.Packager
rdkit.ML.NaiveBayes
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rdkit.ML.NaiveBayes.ClassificationModel
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Defines Naive Baysean classification model...
rdkit.ML.NaiveBayes.CrossValidate
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handles doing cross validation with naive bayes models...
rdkit.ML.Neural
rdkit.ML.Neural.ActFuncs
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Activation functions for neural network nodes
rdkit.ML.Neural.CrossValidate
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handles doing cross validation with neural nets
rdkit.ML.Neural.NetNode
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Contains the class _NetNode_ which is used to represent nodes in neural nets
rdkit.ML.Neural.Network
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Contains the class _Network_ which is used to represent neural nets
rdkit.ML.Neural.Trainers
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Training algorithms for feed-forward neural nets
rdkit.ML.SLT
rdkit.ML.SLT.Risk
:
code for calculating empirical risk
rdkit.ML.Scoring
rdkit.ML.Scoring.Scoring
:
$Id$
rdkit.ML.ScreenComposite
:
command line utility for screening composite models
rdkit.ML.files
:
Generic file manipulation stuff
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