Data Mining by Mehmed Kantardzic (inspirational novels TXT) 📗
- Author: Mehmed Kantardzic
Book online «Data Mining by Mehmed Kantardzic (inspirational novels TXT) 📗». Author Mehmed Kantardzic
N-dimensional data
N-dimensional space
N-dimensional visualization
N-fold cross-validation
Necessity measure
Negative border
Neighbor number (NN)
Neuro-Fuzzy system
Nominal scale
Normalization
NP hard problem
Null hypothesis
Objective function
Observational approach
OLAP (Online analytical processing)
Optimization
Ordinal scale
Outlier analysis
Outlier detection
Outlier detection, distance based
Overfitting (overtraining)
PageRank algorithm
Parabox
Parallel coordinates
Parameter identification
Partially matched crossover (PMC)
Partitional clustering
Pattern
Pattern association
Pattern recognition
Pearson correlation coefficient
Perception
Perceptron
Pie chart
Piecewise aggregate approximation (PAA)
Pixel-oriented visualization
Population
Possibility measure
Postpruning
Prediction
Predictive accuracy
Predictive data mining
Predictive regression
Prepruning
Principal Component Analysis (PCA)
Principal components
Projected database
Pruning decision tree
Radial visualization (Radviz)
Random variable
Rao’s coefficient
Ratio scale
Ratios
Receiver operating characteristic (ROC)
Receiver operating characteristic (ROC) curve
Regression
Logistic
Linear
Nonlinear
Multiple
Regression equation
Resampling methods
Resubstitution method
Return on investment (ROI) chart
Risk functional
Rotation method
RuleExchange
RuleGeneralization
RuleSpecialization
RuleSplit
Sample
Sampling
average
incremental
inverse
random
stratified
systematic
Saturating linear function
Scaling
Scatter plot
Schemata
fitness
length
order
Scientific visualization
Scrubbing
Sensitivity
Sequence
Sequence mining
Sequential pattern
Similarity measure
Simple matching coefficient (SMC)
Single-link method
Smoothing data
Spatial data mining
Autoregressive model
Spatial outlier
Specificity
Split-info function
SQL (Structured query language)
SSE (Sum of squares of the errors)
Standard deviation
Star display
Statistics
Statistical dependency
Statistical inference
Statistical learning theory (SLT)
Statistical methods
Statistical testing
Stochastic approximation
Stopping rules
Strong rules
Structure identification
Structural risk minimization (SRM)
Summarization
Supervised learning
Support
Survey plot
Survival data
Synapse
System identification
Tchebyshev distance
Temporal data Mining
Sequences
Time series
Test of hypothesis
Testing sample
Text analysis
Text database
Text mining
Text-refining
Time lag (time window)
Time series, multivariate
Time series, univariate
Training sample
Transduction
Traveling salesman problem (TSP)
Trial and error
True risk functional
Ubiquitous data mining
Underfitting
Unobserved inputs
Unsupervised learning
Value reduction
Variables
continuous
discrete
categorical
dependent
independent
nominal
numeric
ordinal
periodic
unobserved
Variance
Variogram cloud technique
Vapnik-Chervonenkis (VC) theory
Vapnik-Chervonenkis (VC) dimension
Visual clustering
Visual data mining
Visualization
Visualization tool
Voronoi diagram
Web mining
content
HITS(Hyperlink-Induced Topic Search) algorithm
LOGSOM algorithm
path-traversal patterns
structure
usage
Web page content
Web page design
Web page quality
Web site design
Web site structure
Widrow-Hoff rule
Winner-take-all rule
XOR problem
Comments (0)