Data Mining Charu C Aggarwal

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Index

χ 2 Measure

_ -diversity

k -anonymity

t -closeness

AdaBoost

Agglomerative Clustering

Aggregate Change Points

Almost Closed Sets

AMS Sketch

Approximate Frequent Patterns

Apriori Algorithm

AR Model

ARIMA Model

ARMA Model

Association Pattern Mining

Association Rule Hiding

Association Rules

Associative Classifiers

Authorities

Autoregressive Integrated Moving Average

Model

Autoregressive Model

Autoregressive Moving Average Model

AVC-set

Bag-of-Words Kernel

Bagging

Balaban Index

Barabasi-Albert Model

Baum-Welch Algorithm

Bayes Classifier

Bayes Optimal Privacy

Bayes Reconstruction Method

Bayes Text Classifier

Behavioral Attributes

Bernoulli Bayes Model

Between-Class Scatter Matrix

Betweenness Centrality

Bias Term in SVMs

Biased Sampling

Big Data

Binarization

Binning of Time Series

Biological Sequences

BIRCH

Bisecting K-Means

Bloom Filter

BOAT

Boosting

Bootstrap

Bootstrapped Aggregating

Bucket of Models

Buckshot

C4.5rules

Candidate Distribution Algorithm

Cascade

Categorical Data Clustering

CBA

Centrality

Centroid Distance Signature

Centroid-based Text Classification

Chebychev Inequality

Chernoff Bound (Lower-Tail)

Chernoff Bound (Upper-Tail)

Circuit Rank

CLARA

CLARANS

Classification

Classification Based on Associations

Classification of Time Series

Classifier Evaluation

Classifying Graphs

Cleaning Data

CLIQUE

Closed Itemsets

Closed Patterns

Closeness Centrality

CLUSEQ

Cluster Digest for Text

Cluster Validation

Clustering

Clustering Coefficient

Clustering Data Streams

Clustering Graphs

Clustering Tendency

Clustering Text

Clustering Time Series

Clusters and Outliers

CluStream

Co-clustering

Co-clustering for Recommendations

Co-location Patterns

Co-Training

Coefficient of Determination

Collaborative Filtering

Collective Classification

Combination Outliers in Sequences

Community Detection

Compression-based Dissimilarity Measure,

513

Concept Drift

Condensation-based Anonymization

Confidence

Confidence Monotonicity

Constrained Clustering

Constrained Pattern Mining

Constrained Sequential Patterns

Content-based Recommendations

Contextual Attributes

CONTOUR

Coordinate Descent

Core of Joined Subgraphs

Count-Min Sketch

Cross-Validation

CSketch

CURE

CVFDT

Cyclomatic Number

Data Classification

Data Cleaning

Data Clustering

Data Reduction

Data Streams

Data Type Portability

Data Types, 6

Data-centered Ensembles

DBSCAN

Decision List

Decision Trees

Degree Centrality

Degree Prestige

DENCLUE

Dendrogram

Densification

Density Attractors

DepthProject Algorithm

Differencing Time Series

Diffusion Models

Dijkstra Algorithm

Dimensionality Curse in Privacy

Dimensionality Reduction

Discrete Cosine Transform

Discrete Fourier Transform

Discrete Sequence Similarity Measures

Discretization

Discriminative Classifier

Distance-based Clustering

Distance-based Entropy

Distance-based Motifs

Distance-based Outlier Detection

Distance-based Sequence Clustering

Distance-based Sequence Outliers

Distributed Privacy

Document Preparation

Document-Term Matrix, 8

Domain Generalization Hierarchy

Downward Closure Property

DWT

Dynamic Programming in HMM

Dynamic Time Warping Distance

Dynamics of Network Formation

Early Termination Trick

Earth Mover Distance

Eckart-Young Theorem

Eclat

Edit Distance

Edit Distance in Graphs

Eigenvector Centrality

EM Algorithm for Continuous Data

EM Algorithm for Data Clustering

Embedded Models

Energy of a Data Set

Ensemble Classification

Ensemble Clustering

Ensemble-based Streaming Classification

Entropy

Entropy _ -diversity

Enumeration Tree

Equivalence Class in Privacy

Error Tree of Wavelet Representation

Estrada Index

Euclidean Metric

Event Detection

Evolutionary Outlier Algorithms

Example Re-weighting

Expected Error Reduction

Expected Model Change

Expected Variance Reduction

Explaining Sequence Anomalies

Exponential Smoothing

Extreme Value Analysis

Feature Bagging

Feature Selection

Feature Selection for Classification

Feature Selection for Clustering

Filter Models

Finite State Automaton

First Story Detection

Fisher Score

Fisher’s Linear Discriminant

Flajolet-Martin Algorithm

FOIL’s Information Gain

Forward Algorithm

Forward-backward Algorithm

Fowlkes-Mallows Measure

Fractionation

Frequency-based Sequence Outliers

Frequent Itemset

Frequent Pattern Mining

Frequent Pattern Mining in Streams

Frequent Substructure Mining

Frequent Trajectory Paths

Frequent Traversal Patterns

Full-Domain Generalization

Generalization in Privacy

Generalization Property

Generalized Linear Models

Generative Classifier

Geodesic Distances

Gini Index

Girvan-Newman Algorithm

GLM

Global Recoding

Global Statistical Similarity

Goodall Measure

Graph Classification

Graph Clustering

Graph Database

Graph Distances and Matching

Graph Edit Distance

Graph Isomorphism

Graph Kernels

Graph Matching

Graph Similarity Measures

Graph-based Algorithms

Graph-based Collaborative Filtering

Graph-based Methods

Graph-based Semisupervised Learning

Graph-based Sequence Clustering

Graph-based Spatial Neighborhood

Graph-based Spatial Outliers

Graph-based Time-Series Clustering

Gregariousness in Social Networks

Grid-based Outliers

Grid-based Projected Outliers

GSP Algorithm

Haar Wavelets

Heavy Hitters

Hidden Markov Model Clustering

Hidden Markov Models

Hierarchical Clustering Algorithms

High Dimensional Privacy

Hinge Loss

Histogram-based Outliers

HITS

HMETIS

HMM

HMM Applications

Hoeffding Inequality

Hoeffding Trees

Holdout

Homophily

Hopkin’s Statistic

Hosoya Index

HOTSAX

Hubs

Hybrid Feature Selection

Imputation

Incognito

Incognito Super-roots

Inconsistent Data

Independent Cascade Model

Independent Ensembles

Inductive Classifiers

Influence Analysis

Information Gain

Information Theoretic Measures

Instance-based Learning

Instance-based Text Classification

Interest Ratio

Internal Validation Criteria

Intrinsic Dimensionality

Inverse Document Frequency

Inverse Occurrence Frequency

Inverted Index

ISOMAP

Item-based Recommendations

Itemset

Iterative Classification Algorithm

Jaccard Coefficient

Jaccard for Multiway Similarity

K-Means

K-Medians

K-Medoids

K-Modes

Katz Centrality

Kernel Density Estimation

Kernel Fisher’s Discriminant

Kernel K-Means

Kernel Logistic Regression

Kernel PCA

Kernel Ridge Regression

Kernel SVM

Kernel Trick

Kernels in Graphs

Kernighan-Lin Algorithm

Keyword-based Sequence Similarity

Kruskal Stress

Label Propagation Algorithm

Lagrangian Optimization in NMF

Large Itemset

Lasso

Latent Components of NMF

Latent Components of SVD

Latent Factor Models

Latent Semantic Indexing

Law Enforcement

Lazy Learners

Learn-One-Rule

Leave-One-Out Bootstrap

Leave-One-Out Cross-Validation

Left Eigenvector

Level-wise Algorithms

Levenshtein Distance

Lexicographic Tree

Likelihood Ratio Statistic

Linear Discriminant Analysis

Linear Threshold Model

Link Prediction

Link Prediction for Recommendations

Loadshedding

Local Outlier Factor

Local Recoding

LOF

Logistic Regression

Longest Common Subsequence

Lookahead-based Pruning

Lossy Counting Algorithm

LSA

MA Model

Macro-clustering

Mahalanobis k -means

Mahalanobis Distance

Manhattan Metric

Margin

Margin Constraints

Markov Inequality

Massive-Domain Stream Clustering

Massive-Domain Streaming Classification

Match-based Distance Measures in Graphs

Maximal Frequent Itemsets

Maximum Common Subgraph

Maximum Common Subgraph Problem

Mean-Shift Clustering

Mercer Kernel Map

Mercer’s Theorem

METIS

Metric

Micro-clustering

Min-Max Scaling

Minkowski Distance

Missing Data

Missing Time-Series Values

Mixture Modeling

Model Selection

Model-centered Ensembles

Mondrian Algorithm

Moore-Penrose Pseudoinverse

Morgan Index

Motif Discovery

Moving Average Model

Moving Average Smoothing

Multiclass Learning

Multidimensional Change Points

Multidimensional Scaling

Multidimensional Spatial Neighborhood

Multidimensional Spatial Outliers

Multilayer Neural Network

Multinomial Bayes Model

Multivariate Extreme Values

Multivariate Time Series

Multivariate Time-Series Forecasting

Multiview Clustering

Naive Bayes Classifier

NCSA Common Log Format

Near Duplicate Detection

Nearest Neighbor Classifier

Neighborhood-based Collaborative Filtering

Network Data

Neural Networks

NMF

Node-Induced Subgraph

Noise Removal from Time Series

Non-stationary Time Series

Nonlinear Regression

Nonlinear Support Vector Machines

Nonnegative Matrix Factorization

Normalization

Normalization of Time Series

Normalized Wavelet Basis

Novelties in Text

Oblivious Transfer Protocol

One-Against-One Multiclass Learning

One-Against-Rest Multiclass Learning

Online Novelty Detection

Online Time-Series Clustering

ORCLUS

Ordered Probit Regression

Outlier Analysis

Outlier Detection

Outlier Ensembles

Outlier Validity

Output Privacy

Overfitting

PAA

PageRank

Partial Periodic Patterns

Partition Algorithm

Partition-1

PCA

Perceptron

Periodic Patterns

Perturbation for Privacy

Pessimistic Error Rate

Piecewise Aggregate Approximation

PLSA

Point Outliers in Time Series

Poisson Regression

Polynomial Regression

Pool-based Active Learning

Position Outliers in Sequences

Power-Iteration Method

Power-Law Degree Distribution

Predictive Attribute Dependence

Preferential Attachment

Preferential Crawlers

Prestige

Principal Component Analysis

Principal Components Regression

Privacy-Preserving Data Mining

Privacy-Preserving Data Publishing

Probabilistic Classifiers

Probabilistic Clustering

Probabilistic Latent Semantic Analysis

Probabilistic Outlier Detection

Probabilistic Suffix Trees

Probabilistic Text Clustering

Probit Regression

PROCLUS

Product Graph

Profile Association Rules

Projected Outliers

Projection-based Reuse

Projection-based Reuse of Support Counting,

107

Proximal Gradient Methods

Proximity Models for Mixed Data

Proximity Prestige

PST

Pyramidal Time Frame

Query Auditing

Query-by-Committee

Querying Patterns

QuickSI Algorithm

RainForest

Randic Index

Random Forests

Random Subspace Ensemble

Random Subspace Sampling

Random Walks

Random-Walk Kernels

Randomization for Privacy

Rank Prestige

Ranking Algorithms

Rare Class Learning

Ratings Matrix

Recommendations

Recommender Systems

Recursive ( c, _ )-diversity

Regression Modeling

Regularization

Regularization in Collective Classification

Rendezvous Label Propagation

Representative-based Clustering

Representativeness-based Active Learning

Reservoir Sampling

Response Variable

Ridge Regression

Right Eigenvector

RIPPER

Rocchio Classification

ROCK

Samarati’s Algorithm

Sampling

SAX

Scalable Classification

Scalable Clustering

Scalable Decision Trees

Scale-Free Networks

Scaling

Scatter Gather Text Clustering

Secure Multi-party Computation

Secure Set Union Protocol

Selective Sampling

Self Training

Semisupervised Bayes Classification

Semisupervised Clustering

Semisupervised Learning

Sensor-Selection

Sequence Classification

Sequence Data

Sequence Outlier Detection

Sequential Covering Algorithms

Sequential Ensembles

Sequential Pattern Mining

Shape Analysis

Shape Clustering

Shape Outliers

Shape-based Time-Series Clustering

Shared Nearest Neighbors

Shingling

Short Memory Property

Shortest Path Kernels

Shrinking Diameters

Signature Table

Similarity Computation with Mixed Data

Simple Matching Coefficient

Simple Redundancy

SimRank

Singular Value Decomposition

Small World Networks

SMOTE

Social Influence Analysis

Soft SVM

Spatial Co-location Patterns

Spatial Data

Spatial Data Mining

Spatial Outliers

Spatial Tile Transformation

Spatial Wavelets

Spatiotemporal Data

Spectral Clustering

Spectral Decomposition

Spectral Methods in Collective Classification,

646

Spectrum Kernel

Spider Traps

Spiders

SPIRIT

Stacking

Standardization

Stationary Time Series

Stop-word Removal

STORM

Stratified Cross-Validation

Stratified Sampling

STREAM Algorithm

Streaming Classification

Streaming Data

Streaming Frequent Pattern Mining

Streaming Novelty Detection

Streaming Outlier Detection

Streaming Privacy

Streaming Synopsis

Strict Redundancy

String Data

Subgraph Isomorphism

Subgraph Matching

Subsequence

Subsequence-based Clustering

Superset-based Pruning

Supervised Feature Selection

Supervised Micro-clusters for Classification

Support

Support Vector Machines

Support Vectors

Suppression in Privacy

SVD

SVM for Text

SVMLight

SVMPerf

Symbolic Aggregate Approximation

Symmetric Confidence Measure

Synopsis for Streams

Synthetic Data for Anonymization

Synthetic Over-sampling

System Diagnosis

Tag Trees

TARZAN

Temporal Similarity Measures

Term Strength

Text Classification

Text Clustering

Text SVM

Tikhonov Regularization

Time Series Similarity Measures

Time Warping

Time-Series Classification

Time-Series Correlation Clustering

Time-Series Data, 9

Time-Series Data Mining

Time-Series Forecasting

Time-Series Preparation

Topic Modeling

Topic-Sensitive PageRank

Topological Descriptors

Trajectory Classification

Trajectory Clustering

Trajectory Mining

Trajectory Outlier Detection

Trajectory Pattern Mining

Transductive Classifiers

Transductive Support Vector Machines

TreeProjection Algorithm

Triadic Closure

Ullman’s Isomorphism Algorithm

Uncertainty Sampling

Universal Crawlers

Unsupervised Feature Selection

User-based Recommendations

Utility in Privacy

Utility Matrix

Value Generalization Hierarchy

Velocity Density Estimation

Vertical Counting Methods

VF2 Algorithm

Viterbi Algorithm

Ward’s Method

Wavelet-based Rules

Wavelets

Web Crawling

Web Document Processing

Web Resource Discovery

Web Server Logs

Web Usage Mining

Weighted Degree Kernel

Wiener Index

Within-Class Scatter Matrix

Wrapper Models

XProj

XRules

Z-Index