Microsoft.VisualBasic.DataMining.Framework 1.0.9753.4776.

Namespaces 25 Types 93 Members 573

01 Namespaces

Microsoft.VisualBasic.DataMining

Type	Summary	Members
MarginalLikelihoodAnalysis	@author Marc Suchard @author Alexei Drummond Source translated from model_P.c (a component of BAli-Phy by Benjamin Redelings and Marc Suchard	12
SelfOrganizingMap	SOM: Self-Organizing Map	8
Standardizer	每维度特征的 z-score 标准化器。训练阶段按特征维计算均值/标准差，推理阶段复用同一套参数，解决各维度特征量纲差异大导致的梯度不稳定问题。零方差维度标准差置 1，避免除零。	6
Statistics	Set of statistics functions.	6
ValueMapping		7

Microsoft.VisualBasic.DataMining.AprioriRules

Type	Summary	Members
AprioriExport	AprioriRules API export module	2
Encoding	Transaction encoding helper.(对一个Transaction之中的独立部件编码为一个字符)	6
Item	mapping the Item.Item string comparision to Item.Code comparision	9
ItemSet		18

Microsoft.VisualBasic.DataMining.AprioriRules.Entities

Type	Summary	Members
Output		6
Rule		10
Transaction	a transaction record	4

Microsoft.VisualBasic.DataMining.AprioriRules.Impl

Type	Summary	Members
Apriori	关联分析程序（当某一种事务的样本较少的时候，将无法分析出关联性）	11

Microsoft.VisualBasic.DataMining.Clustering

Type	Summary	Members
CanopyBuilder	initial for k-means	7
ClusteringTableExtensions	统一的二维表聚类扩展入口集合。这里的每一个扩展方法都以经过预处理之后的纯数值二维表NumericTable 作为数据输入，并且将聚类结果写入标签矩阵，最终返回写入结果之后的原表对象。	15
Density	evaluate point density	4
KNN	KNN classifier	4
Mark		4
NumericRow	数值行对象：包装统一二维表NumericTable之中的一行数值数据，同时携带样本 ID 与该行在原始表之中的下标。该对象用于在不修改既有泛型聚类算法内部实现的前提之下，让这些算法直接消费二维表的数值行。	4
Spectral	Spectral Clustering	12

Microsoft.VisualBasic.DataMining.ComponentModel

Type	Summary	Members
EntityBase	An abstract property vector	4
IDataEmbedding		2
IntegerEntity	{Properties} -> Class	4
TraceBackAlgorithm		2
TraceBackIterator	A helper module for record the clustering traceback information for run algorithm debug	8

Microsoft.VisualBasic.DataMining.ComponentModel.Discretion

Type	Summary	Members
Discretizer	通过这个对象来执行对连续性数值的数据集的离散化操作	7
NormalRangeDiscretizer	对原始数据进行区间离散化	6

Microsoft.VisualBasic.DataMining.ComponentModel.Encoder

Type	Summary	Members
ClassEncoder		11
ColorClass	Object entity classification class	16

Microsoft.VisualBasic.DataMining.ComponentModel.Encoder.Variable

Type	Summary	Members
Binary		2

Microsoft.VisualBasic.DataMining.ComponentModel.EntityModels

Type	Summary	Members
ClusterEntity	A tagged numeric vector	12
EntityClusterModel	存储在Csv文件里面的数据模型，近似等价于csv DataSet对象，只不过多带了一个用来描述cluster的EntityClusterModel.Cluster 属性标签	7

Microsoft.VisualBasic.DataMining.ComponentModel.Normalizer

Type	Summary	Members
Methods		6
Normalizations		3

Microsoft.VisualBasic.DataMining.ComponentModel.Serialization

Type	Summary	Members
EntityVectorFile	helper module for IPC parallel or store the result data	4

Microsoft.VisualBasic.DataMining.DBSCAN

Type	Summary	Members
DbscanAlgorithm	DBSCAN algorithm class, Density-based spatial clustering of applications with noise (DBSCAN)	2
DbscanPoint		6
DbscanSession		10

Microsoft.VisualBasic.DataMining.DecisionTree

Type	Summary	Members
Algorithm	Algorithm module for train a new decision tree model	2
Attributes	Node attribute value	5
Tree	Implementation of the ID3 to create a decision tree > https://github.com/WolfgangOfner/DecisionTree	7
VisualDebugger	Display debug info on console	2

Microsoft.VisualBasic.DataMining.DecisionTree.Data

Type	Summary	Members
DataImports		2
DataTable	训练集样本数据表	7
Entity	A row in data table.(分类用的对象实例)	3

Microsoft.VisualBasic.DataMining.DFL_Driver

Type	Summary	Members
dflNode	A node in the fuzzy logic network.(模糊逻辑网络之中的一个节点)	3
I_FactorElement	This object represents the factor which decides the node state changes.(决定dflNode的状态的因素)	10

Microsoft.VisualBasic.DataMining.Evaluation

模型质量评估工具模块

Type	Summary	Members
FakeAUCGenerator		2
Metrics		11
PerformanceEvaluator	Class which evaluates an SVM model using several standard techniques.	5
RankPair	Class encoding a member of a ranked set of labels.	5
RegressionClassify	The regression classifier result.	5
RegressionROC		2
ROC	The ROC math module	4
Validate	一个包含有多维度验证结果输出的样本验证结果	7
Validation	验证结果描述灵敏度 = 真阳性人数 / (真阳性人数 + 假阴性人数) * 100% 特异度 = 真阴性人数 / (真阴性人数 + 假阳性人数) * 100%	28

Microsoft.VisualBasic.DataMining.FuzzyCMeans

Type	Summary	Members
CMeans	the cmeans algorithm module Fuzzy clustering (also referred to as soft clustering) is a form of clustering in which each data point can belong to more than one cluster.	7
CMeansEngine	基于数值行（Double()）的模糊 C 均值聚类引擎。该引擎直接消费NumericTable的特征矩阵，不再依赖 ClusterEntity 实体对象，运算结果（隶属度矩阵与硬划分结果）可以写回标签矩阵。	3
CMeansResult	模糊 C 均值聚类的数值计算结果	3
FuzzyCMeansEntity	A numeric vector object that tagged with the fuzzy cmeans cluster membership values	4

Microsoft.VisualBasic.DataMining.HDBSCAN.Distance

Type	Summary	Members
CosineSimilarity	Computes cosine similarity between two points, d = 1 - ((XY) / (\|\|X\|\|\|\|Y\|\|))	2
EuclideanDistance	Computes the euclidean distance between two points, d = sqrt((x1-y1)^2 + (x2-y2)^2 + ...	1
IDistanceCalculator	An interface for classes which compute the distance between two points (where points are represented as arrays of doubles).	1
ISparseMatrixSupport		1
ManhattanDistance	Computes the manhattan distance between two points, d = \|x1-y1\| + \|x2-y2\| + ...	1
PearsonCorrelation	Computes the euclidean distance between two points, d = 1 - (cov(X,Y) / (std_dev(X) * std_dev(Y)))	1
SupremumDistance	Computes the supremum distance between two points, d = max[(x1-y1), (x2-y2), ...	1

Microsoft.VisualBasic.DataMining.HDBSCAN.Hdbscanstar

Type	Summary	Members
Cluster	An HDBSCAN* cluster, which will have a birth level, death level, stability, and constraint satisfaction once fully constructed.	15
HdbscanAlgorithm		8
HdbscanConstraint	A clustering constraint (either a must-link or cannot-link constraint between two points).	4
OutlierScore	Simple storage class that keeps the outlier score, core distance, and id (index) for a single point.	4
UndirectedGraph	An undirected graph, with weights assigned to each edge.	11

Microsoft.VisualBasic.DataMining.Kernel.BayesianBeliefNetwork

Type	Summary	Members
BeliefNetwork	贝叶斯信念网络	4
BeliefNode	贝叶斯信念网络中的一个节点	10
BElim		1

Microsoft.VisualBasic.DataMining.Kernel.Classifier

Type	Summary	Members
Bayesian	朴素贝叶斯分类器	6
Neuron	朴素神经元分类器,只能够进行一些简单的分类工作	6

Microsoft.VisualBasic.DataMining.KMeans

Type	Summary	Members
Cluster	A collection of the target entity object will be a cluster	4
ClusterCollection	A collection of Cluster objects or Clusters	5
Evaluation	判断聚类结果优劣的两个距离判定方法	13
EvaluationScore		12
Extensions		5
KMeansAlgorithm	This class implement a KMeans clustering algorithm.	6
KMeansCluster	A class containing a group of data with similar characteristics (cluster), KMeans Cluster	10
KMeansEngine	基于统一二维表NumericTable的 KMeans 聚类引擎。算法直接消费数值行（Double()）而不再依赖 EntityBase 实体对象，运算结果可以方便的写入NumericTable.labels标签矩阵之中。	5
Kmedoids	Partitioning around medoids(PAM)	3
NumericCluster	统一二维表聚类所使用的数值簇对象。和旧的泛型版本Cluster不一样的地方在于：这个簇对象直接存放数值行（Double数组）以及该行在原始表中的下标与行名，因此不再依赖EntityBase实体对象。	8
NumericClusterCollection	NumericKMeansCluster 的集合，表示一次 KMeans 运算结果之中的全部簇。	5
NumericKMeansCluster	统一二维表聚类所使用的 KMeans 簇对象，直接基于数值行进行均值与代价计算。	9

Microsoft.VisualBasic.DataMining.KMeans.Bisecting

Type	Summary	Members
BisectingKMeans	Created by touhid on 12/21/15.	5
Cluster	Created by touhid on 12/21/15.	8

Microsoft.VisualBasic.DataMining.Lloyds

Type	Summary	Members
Clustering		2
LloydsMethodClustering	Voronoi	2