Index
A
- abline function / Regression line
- abline function, parameters
- a / Regression line
- b / Regression line
- untf / Regression line
- h / Regression line
- v / Regression line
- coef / Regression line
- reg / Regression line
- acf function
- used, for creating correlogram / Correlogram
- acf function, parameters
- x / Correlogram
- lag.max / Correlogram
- type / Correlogram
- plot / Correlogram
- na.action / Correlogram
- demean / Correlogram
- AdaBoost / AdaBoost
- ada package / Packages, AdaBoost
- affinity propagation clustering
- about / Affinity propagation clustering
- airport data, Washington University survey
- anomaly detection
- about / Anomaly detection
- outliers, displaying / Show outliers
- anomalies, calculating / Calculating anomalies
- usage / Usage
- example / Example 1, Example 2
- apcluster function
- about / Affinity propagation clustering
- apcluster package
- about / Packages
- apriori
- about / Apriori
- usage / Usage
- example / Evaluating associations in a shopping basket
- apriori rules library
- ARIMA
- about / ARIMA
- using / ARIMA
- used, for automated forecasting / Automated ARIMA forecasting
- arima function, parameters
- arulesNBMiner
- about / arulesNBMiner
- usage / Usage
- example / Mining the Agrawal data for frequent sets
- association rules
- about / Association rules
- support / Association rules
- confidence / Association rules
- lift / Association rules
- apriori rules library, using / Mine for associations
- usage / Usage
- example / Example
- automatic forecasting packages
- about / Automatic forecasting packages
- forecast / Automatic forecasting packages
- TTR / Automatic forecasting packages
- Auto MPG dataset
B
- bar3d function
- about / vrmlgenbar3D
- bar3d function, parameters
- data / vrmlgenbar3D
- row.labels, col.labels / vrmlgenbar3D
- filename / vrmlgenbar3D
- type / vrmlgenbar3D
- bar chart
- bar charts
- about / Bar charts and plots
- bar plot
- about / Bar plot
- barplot function
- barplot function, parameters
- Bayesian information
- cluster, selecting based on / Selecting clusters based on Bayesian information
- Bayesian learning
- about / Bayesian learning
- big.matrix function, parameters
- Big Data, R
- bigmemory package
- about / bigmemory
- bioconductor.org / bioconductor
- bivariate binning display / Bivariate binning display
- blind signal separation / Blind signal separation
- Box.test function, parameters
- boxplot function
- about / Show outliers, Example
- Box test
- using / Box test
- build phase, K-medoids clustering
- about / K-medoids clustering
- bw function
C
- calinski criterion graph
- about / The cascadeKM function
- caret package / Packages
- about / Data partitioning, Packages
- car package
- cascadeKM function
- about / The cascadeKM function
- cascadeKM function, parameters
- data / The cascadeKM function
- inf.gr / The cascadeKM function
- sup.gr / The cascadeKM function
- iter / The cascadeKM function
- criterion / The cascadeKM function
- chart.Correlation function, parameters
- R / Visualizing correlations
- histogram / Visualizing correlations
- method / Visualizing correlations
- chemometrics
- about / Multivariate regression analysis
- problems / Multivariate regression analysis
- chemometrics package
- about / Packages
- classIn package / Packages
- class package / Packages
- cloud3d function
- cloud function
- about / Lattice Cloud – 3D scatterplot
- used, for producing 3D scatterplot / Lattice Cloud – 3D scatterplot
- clue package / Packages
- clusGap function
- clusGap function, parameters
- cluster
- selecting, based on Bayesian information / Selecting clusters based on Bayesian information
- cluster analysis
- K-means clustering / K-means clustering
- K-medoids clustering / K-medoids clustering
- hierarchical clustering / Hierarchical clustering
- expectation maximization (EM) / Expectation-maximization
- density estimation / Density estimation
- about / Cluster analysis
- cluster analysis, model
- connectivity / Cluster analysis
- partitioning / Cluster analysis
- distribution models / Cluster analysis
- density / Cluster analysis
- connectivity model
- about / Cluster analysis
- copula package
- about / Packages
- cor.test function, parameters
- x / Covariance
- y / Covariance
- alternative / Covariance
- method / Covariance
- exact / Covariance
- continuity / Covariance
- cor function
- used, for performing correlation / Correlation
- cor function, parameters
- x / Correlation
- y / Correlation
- use / Correlation
- method / Correlation
- corpus
- about / Example
- creating / Creating a corpus
- text, converting to lower case / Converting text to lowercase
- punctuation, removing / Removing punctuation
- numbers, removing / Removing numbers
- words, removing / Removing words
- whitespaces, removing / Removing whitespaces
- word stems / Word stems
- document term matrix / Document term matrix
- VectorSource, using / Using VectorSource
- correlation
- about / Correlation
- performing, cor function used / Correlation
- example / Example
- correlation functionality
- packages / Packages
- correlations
- visualizing, corrgram() function used / Visualizing correlations
- correlogram
- creating, acf function used / Correlogram
- corrgram() function
- used, for visualizing correlations / Visualizing correlations
- corrgram tool
- about / Packages
- Cortona
- about / cloud3d
- covariance
- measuring, cov function used / Covariance
- cov function
- used, for measuring covariance / Covariance
- cpairs function
- used, for plotting matrix data / cpairs – plot matrix data
- createDataPartition function / Instance-based learning
D
- 3D graphics
- generating / Generating 3D graphics
- 3D plotting functionality
- packages / Packages
- 3D scatterplot
- producing, cloud function used / Lattice Cloud – 3D scatterplot
- data
- patterns, determining / Patterns
- data partitioning
- about / Data partitioning
- dataset
- about / Dataset
- DBSCAN function
- about / Density estimation
- decision tree
- about / Decision tree
- decision trees / Decision trees
- decompose function
- about / The decompose function
- density estimation
- about / Density estimation, Density estimation
- Parzen windows / Density estimation
- vector quantization / Density estimation
- histograms / Density estimation
- usage / Usage
- example / Example
- density function
- density model
- about / Cluster analysis
- density scatter plots
- about / Density scatter plots
- distribution models
- about / Cluster analysis
- DMwR package
- about / Example 2
- document term matrix
- about / Document term matrix
E
- e1071 package / Packages
- about / Packages
- ECControl, parameter
- Eclat
- about / Eclat
- usage / Usage
- used, for finding similarities in adult behavior / Using eclat to find similarities in adult behavior
- frequent items, finding in dataset / Finding frequent items in a dataset
- example / An example focusing on highest frequency
- eclat function, parameters
- ECParameters
- elbow / Optimal number of clusters
- ensemble learning / Ensemble learning
- ets function
- using / Automated forecasting
- ets function, parameters
- y / Automated forecasting
- model / Automated forecasting
- damped / Automated forecasting
- beta / Automated forecasting
- alpha / Automated forecasting
- phi / Automated forecasting
- gamma / Automated forecasting
- / Automated forecasting
- expectation-maximization (EM) / Expectation-maximization
- expectation maximization (EM)
- about / Expectation-maximization
- usage / Usage
- example / Example
- exponential smoothing
- using / Exponential smoothing
F
- facet_grid function / The ggplot2 package
- FactoMineR package
- about / Packages
- findAssocs function
- about / Using VectorSource
- forecast package
- about / Automatic forecasting packages, Forecast
- correlogram / Correlogram
- Box test, using / Box test
- fpc package
- about / Packages, Medoids clusters
G
- gap statistic
- used, for estimating cluster count / Gap statistic to estimate the number of clusters
- gbd2dmat function, parameters
- x / Distribute a matrix across nodes
- skip.balance / Distribute a matrix across nodes
- comm / Distribute a matrix across nodes
- gbd.major / Distribute a matrix across nodes
- bldim / Distribute a matrix across nodes
- gclus package
- about / Packages
- getElem function
- about / Using VectorSource
- GetMap.bbox function, parameters
- lonR / RgoogleMaps
- latR / RgoogleMaps
- center / RgoogleMaps
- size / RgoogleMaps
- destfile / RgoogleMaps
- MINIMUMSIZE / RgoogleMaps
- RETURNIMAGE / RgoogleMaps
- GRAYSCALE / RgoogleMaps
- NEWMAP / RgoogleMaps
- zoom / RgoogleMaps
- verbose / RgoogleMaps
- SCALE / RgoogleMaps
- maptype / RgoogleMaps
- ggm function / Packages
- ggplot2 package / Packages, ggplot2
- about / The ggplot2 package, Packages
- used, for producing scatter plots / The ggplot2 package
- ggplot package
- used, for producing histogram / The ggplot2 package
- glucs package / cpairs – plot matrix data
- Google Maps
- about / Google Maps
- gpclib package / Packages
- GTK+ toolkit
- invoking, playwith function used / Interactive graphics
H
- hard clustering
- about / Cluster analysis
- hclust function
- heterogeneous correlation matrix
- generating / A heterogeneous correlation matrix
- hexbin function
- about / Bivariate binning display
- used, for organizing bivariate data / Bivariate binning display
- hexbin function, parameters
- x, y / Bivariate binning display
- xbins / Bivariate binning display
- shape / Bivariate binning display
- xbnds, ybnds / Bivariate binning display
- xlab, ylab / Bivariate binning display
- hexbin package / Packages, Density scatter plots
- hidden Markov models (HMM) / Hidden Markov models
- hierarchical clustering
- about / Hierarchical clustering, Hierarchical clustering
- agglomerative (or bottom up) / Hierarchical clustering
- divisive (or top down) / Hierarchical clustering
- usage / Usage
- example / Example
- histograms
- about / Density estimation
- Hmisc
- about / Packages
- Holt exponential smoothing
- about / Holt exponential smoothing
- ets function, using / Automated forecasting
- ARIMA / ARIMA
- HoltWinters function, parameters
- x / Exponential smoothing
- alpha / Exponential smoothing
- beta / Exponential smoothing
- gamma / Exponential smoothing
- seasonal / Exponential smoothing
- / Exponential smoothing
I
- identify function
- about / Show outliers
- initial terrain map
- creating / Google Maps
- instance-based learning
- about / Instance-based learning
- interactive graphics
- about / Interactive graphics
K
- k-means clustering / K-means clustering
- K-means clustering
- about / K-means clustering, K-means clustering
- usage / Usage
- example / Example, Example
- optimal number, of clusters / Optimal number of clusters
- K-medoids clustering
- about / K-medoids clustering
- build phase / K-medoids clustering
- swap phase / K-medoids clustering
- usage / Usage
- example / Example
- k-nearest neighbor classification
- kernlab package / Packages
- about / Packages
- kknn function / Instance-based learning
- kknn package
- about / Packages
- kmeans function
- about / Usage
- x parameter / Usage
- centers parameter / Usage
- iter.max parameter / Usage
- nstart parameter / Usage
- algorithm parameter / Usage
- trace parameter / Usage
- kmeans function, parameters
- x / K-means clustering, Cluster analysis
- centers / K-means clustering, Cluster analysis
- iter.max / K-means clustering
- nstart / K-means clustering
- algorithm / K-means clustering
- trace / K-means clustering
- kmeans object
- knn function / Instance-based learning
- knn function, parameters
- train / Instance-based learning
- test / Instance-based learning
- cl / Instance-based learning
- k / Instance-based learning
- l / Instance-based learning
- prob / Instance-based learning
- use.all / Instance-based learning
L
- lattice package
- latticist package / Packages
- about / The latticist package
- leaf
- about / Decision tree
- least squares regression
- about / Least squares regression
- linear model / Linear model
- line graph
- generating / The ggplot2 package
- lm function / Regression
- lm function, parameter
- formula / Regression
- data / Regression
- subset / Regression
- weights / Regression
- lofactor function
- about / Example 2
- logistic regression / Logistic regression
- longest common prefix (LCP)
- about / Similarities in the sequence
- longest common subsequence (LCS)
- about / Similarities in the sequence
- lowess function / A lowess line
- lowess function, parameters
- x / A lowess line
- y / A lowess line
- f / A lowess line
- iter / A lowess line
- delta / A lowess line
- lowess line
- about / A lowess line
M
- machine learning
- packages / Packages
- mapdata package / Packages
- map function
- about / Mapping
- map function, parameters
- database / Mapping
- regions / Mapping
- exact / Mapping
- boundary / Mapping
- interior / Mapping
- projection / Mapping
- parameters / Mapping
- orientation / Mapping
- fill / Mapping
- col / Mapping
- plot / Mapping
- add / Mapping
- namesonly / Mapping
- xlim, ylim / Mapping
- wrap / Mapping
- resolution / Mapping
- bg / Mapping
- mar / Mapping
- myborder / Mapping
- mapping
- about / Mapping
- maps
- points, plotting on / Plotting points on a map
- maps package / Packages
- about / Mapping
- maptools package / Packages
- MASS package / Packages
- matrix data
- displaying, splom function used / splom – display matrix data
- plotting, cpairs function used / cpairs – plot matrix data
- Mclust function
- about / Usage
- data parameter / Usage
- G parameter / Usage
- modelNames parameter / Usage
- prior parameter / Usage
- control parameter / Usage
- initialization parameter / Usage
- warn parameter / Usage
- univariate mixture dataset / List of model names
- multivariate mixture dataset / List of model names
- single component dataset / List of model names
- mclust package / Selecting clusters based on Bayesian information
- MCMCpack package
- about / Packages
- MCMCregress function / Bayesian learning
- MCMCregress function, parameters
- formula / Bayesian learning
- data / Bayesian learning
- mcv / Neural network
- medoids clusters
- about / Medoids clusters
- microbenchmark package
- about / microbenchmark
- models
- about / Model
- linear model / Linear model
- prediction / Prediction
- logistic regression / Logistic regression
- residuals / Residuals
- least squares regression / Least squares regression
- stepwise regression / Stepwise regression
- k-nearest neighbor classification / The k-nearest neighbor classification
- Naïve Bayes / Naïve Bayes
- Modern Applied Statistics in S+ (MASS)
- about / Robust regression
- monthplot function, parameters
- x / Time series
- labels / Time series
- ylab / Time series
- choice / Time series
- multiple regression
- about / Multiple regression
- multivariate regression analysis
- about / Multivariate regression analysis
N
- Naïve Bayes
- about / Naïve Bayes
- NbClust function / Optimal number of clusters
- NbClust function, parameters
- data / Optimal number of clusters
- diss / Optimal number of clusters
- distance / Optimal number of clusters
- min.nc / Optimal number of clusters
- max.nc / Optimal number of clusters
- method / Optimal number of clusters
- index / Optimal number of clusters
- alphaBeale / Optimal number of clusters
- NbClust package
- about / Packages
- NBMiner function, parameter
- NBMinerParameters, parameter
- neuralnet function / Neural network, Neural network
- neuralnet function, parameter
- formula / Neural network
- data / Neural network
- hidden / Neural network
- stepmax / Neural network
- rep / Neural network
- neuralnet package / Packages
- neural network / Neural network
- about / Neural network
O
- online personality tests
- URL / Polychoric correlation
- OPTICS function
- about / Density estimation
- optimal matching (OM) distance
- about / Similarities in the sequence
- outliers, anomaly detection
- displaying / Show outliers
- example / Example, Example
- anomaly detection example / Another anomaly detection example
P
- packages
- about / Packages
- tm / Packages
- XML / Packages
- text processing / Text processing
- text clusters / Text clusters
- packages, 3D plotting functionality
- packages, clustering functionality
- packages, correlation functionality
- packages, machine learning functionality
- packages, plotting functionalities
- packages, regression analysis
- about / Packages
- simple regression / Simple regression
- multiple regression / Multiple regression
- multivariate regression / Multivariate regression analysis
- robust regression / Robust regression
- packages, supervised/unsupervised learning
- packages, visualization functionality
- pairs function / Covariance
- about / Scatterplot matrices
- pam function
- pamk function
- about / Medoids clusters
- pamk function, parameters
- data / Medoids clusters
- krange / Medoids clusters
- criterion / Medoids clusters
- usepam / Medoids clusters
- scaling / Medoids clusters
- alpha / Medoids clusters
- diss / Medoids clusters
- critout / Medoids clusters
- ns / Medoids clusters
- seed / Medoids clusters
- parallel package
- about / parallel
- parameters, polychor function
- x / Polychoric correlation
- smooth / Polychoric correlation
- global / Polychoric correlation
- polycor / Polychoric correlation
- ML / Polychoric correlation
- std.err / Polychoric correlation
- weight / Polychoric correlation
- progress / Polychoric correlation
- na.rm / Polychoric correlation
- delete / Polychoric correlation
- partial correlation
- producing / Partial correlation
- partitioning model
- about / Cluster analysis
- partitioning rules
- strict / Cluster analysis
- overlapping / Cluster analysis
- hierarchical / Cluster analysis
- Parzen windows
- about / Density estimation
- patterns
- determining, in data / Patterns
- Eclat / Eclat
- arulesNBMiner / arulesNBMiner
- apriori / Apriori
- TraMineR / Determining sequences using TraMineR
- similarities, determining in sequences / Similarities in the sequence
- pbdR project
- about / pbdR
- common global values / Common global values
- data, distributing across nodes / Distribute data across nodes
- matrix across nodes, distributing / Distribute a matrix across nodes
- pdbMPI package / pdbMPI
- Pearson correlations
- producing, rcorr function used / Pearson correlation
- persp function
- about / Generating 3D graphics
- persp function, parameters
- x, y / Generating 3D graphics
- z / Generating 3D graphics
- xlim, ylim, zlim / Generating 3D graphics
- xlab, ylab, zlab / Generating 3D graphics
- main, sub / Generating 3D graphics
- theta, phi / Generating 3D graphics
- r / Generating 3D graphics
- d / Generating 3D graphics
- scale / Generating 3D graphics
- pipes
- about / pipes
- playwith function
- used, for invoking GTK+ toolkit / Interactive graphics
- about / Interactive graphics
- playwith function, parameters
- expr / Interactive graphics
- title / Interactive graphics
- labels / Interactive graphics
- data.points / Interactive graphics
- viewport / Interactive graphics
- parameters / Interactive graphics
- tools / Interactive graphics
- init.actions / Interactive graphics
- prepplot.actions / Interactive graphics
- update.actions / Interactive graphics
- width / Interactive graphics
- height / Interactive graphics
- pointsize / Interactive graphics
- eval.args / Interactive graphics
- on.close / Interactive graphics
- modal / Interactive graphics
- linkto / Interactive graphics
- playstate / Interactive graphics
- plot.call / Interactive graphics
- main.function / Interactive graphics
- playwith package / Packages
- plot function
- about / Scatter plots
- plot function, parameters
- x / Scatter plots
- y / Scatter plots
- type / Scatter plots
- main / Scatter plots
- sub / Scatter plots
- xlab / Scatter plots
- ylab / Scatter plots
- asp / Scatter plots
- points
- plotting, on maps / Plotting points on a map
- plotting, on world map / Plotting points on a world map
- points function, parameters
- polychor function
- about / Polychoric correlation
- parameters / Polychoric correlation
- polychoric correlation
- about / Polychoric correlation
- polycor function / Packages
- polycor package
- about / Polychoric correlation
- pqR package / pqR
- predict function / predict
- prediction / Prediction
- pvclust function
- about / Hierarchical clustering
- pvclust function, parameters
- data / Hierarchical clustering
- method.hclust / Hierarchical clustering
- method.dist / Hierarchical clustering
- use.cor / Hierarchical clustering
- nboot / Hierarchical clustering
- r / Hierarchical clustering
- store / Hierarchical clustering
- weight / Hierarchical clustering
- pvclust package
- about / Packages
Q
R
- randomForest function / Random forests
- randomForest function, parameters
- formula / Random forests
- data / Random forests
- subset / Random forests
- na.action / Random forests
- randomForest package / Packages
- about / Packages
- random forests / Random forests
- about / Random forests
- rattle package
- about / Packages
- RColorBrewer package / Packages
- rcorr function
- used, for producing Pearson correlation / Pearson correlation
- rcorr function, parameters
- x / Pearson correlation
- y / Pearson correlation
- type / Pearson correlation
- Rcpp package
- regression
- about / Regression
- regression line
- adding, to scatter plot / Regression line
- relaimpo package / Packages, Relative importance
- relative importance, of variables
- calculating / Relative importance
- removeSparseTerms function
- about / Using VectorSource
- removeWords function
- about / Using VectorSource
- research areas, R
- about / Research areas
- Rcpp package / Rcpp
- parallel package / parallel
- microbenchmark package / microbenchmark
- pqR package / pqR
- SAP integration / SAP integration
- roxygen2 package / roxygen2
- bioconductor / bioconductor
- swirl package / swirl
- pipes / pipes
- resid function
- about / Residuals
- residuals, models / Residuals
- rgl package
- about / Packages
- RGoogleMaps package / Packages
- about / Google Maps
- RgoogleMaps package
- about / RgoogleMaps
- robust regression
- about / Robust regression
- roxygen2 package
- about / roxygen2
- rpart.plot package
- about / Packages
- rpart function / Decision tree
- rpart function, parameters
- formula / Decision tree
- data / Decision tree
- weights / Decision tree
- subset / Decision tree
- na.action / Decision tree
- method / Decision tree
- R Tools page
- URL / Rcpp
S
- scatter3d function
- scatter plot
- about / Scatter plots
- example / Scatter plots
- regression line, adding to / Regression line
- lowess line / A lowess line
- scatterplot3d function, parameters
- x / scatterplot3d
- y / scatterplot3d
- z / scatterplot3d
- color / scatterplot3d
- scatterplot3d package
- about / scatterplot3d
- used, for generating 3D graphics / scatterplot3d
- scatterplot function / scatterplot
- scatterplot function, parameters
- x / scatterplot
- y / scatterplot
- formula / scatterplot
- data / scatterplot
- subset / scatterplot
- smoother / scatterplot
- smoother.args / scatterplot
- smooth / scatterplot
- span / scatterplot
- spread / scatterplot
- reg.line / scatterplot
- boxplots / scatterplot
- xlab / scatterplot
- ylab / scatterplot
- las / scatterplot
- lwd / scatterplot
- lty / scatterplot
- id.method / scatterplot
- id.n / scatterplot
- id.cex / scatterplot
- id.col / scatterplot
- labels / scatterplot
- log / scatterplot
- jitter / scatterplot
- ylim, ylim / scatterplot
- scatterplot matrices
- about / Scatterplot matrices
- splom function, used for displaying matrix data / splom – display matrix data
- cpairs function, used for plotting matrix data / cpairs – plot matrix data
- scatterplotMatrix() function
- about / Example
- scatter plots
- producing, ggplot2 package used / The ggplot2 package
- seqdef function, parameters
- seqdist function
- used, for determining similarities in sequences / Sequence metrics
- example / Example
- seqdist function, parameters
- seqST function
- sequences
- determining, TraMineR used / Determining sequences using TraMineR
- similarities, determining / Similarities in the sequence
- simple regression
- about / Simple regression
- SMA function
- about / The SMA function
- SMA function, parameters
- snow package
- about / snow
- soft clustering
- about / Cluster analysis
- source
- about / Using VectorSource
- splom() function
- about / Example
- splom() function, parameters
- splom function
- used, for displaying matrix data / splom – display matrix data
- SSE (sum of squared errors)
- about / Exponential smoothing
- stepNext function
- about / Using VectorSource
- stepwise regression
- about / Stepwise regression
- stl function, parameters
- x / Time series
- s.window / Time series
- / Time series
- summary() command
- about / Example
- supervised learning
- about / Supervised learning
- supervised learning, techniques
- decision tree / Decision tree
- regression / Regression
- neural network / Neural network
- instance-based learning / Instance-based learning
- ensemble learning / Ensemble learning
- support vector machines (SVM) / Support vector machines
- Bayesian learning / Bayesian learning
- random forests / Random forests
- Support Vector Machines (SVM) / Support vector machines
- support vector machines (SVM) / Support vector machines
- svm function / Support vector machines
- svm function, parameters
- formula / Support vector machines
- data / Support vector machines
- subset / Support vector machines
- na.action / Support vector machines
- scale / Support vector machines
- swap phase, K-medoids clustering
- about / K-medoids clustering
- swirl package
T
- tetrachoric correlation
- about / Tetrachoric correlation
- running / Tetrachoric correlation
- tetrachoric function, parameters
- x / Tetrachoric correlation
- y / Tetrachoric correlation
- correct / Tetrachoric correlation
- smooth / Tetrachoric correlation
- global / Tetrachoric correlation
- weight / Tetrachoric correlation
- na.rm / Tetrachoric correlation
- delete / Tetrachoric correlation
- text clusters
- about / Text clusters
- word graphics / Word graphics
- XML text, analyzing / Analyzing the XML text
- text operations
- text processing
- about / Text processing
- example / Example
- corpus, creating / Creating a corpus
- text variable
- about / Example
- time series
- about / Time series
- Titanic survival information
- URL / Tetrachoric correlation
- tm package
- about / Packages
- tm_map function
- about / Using VectorSource
- train method
- about / The train Method
- train method, parameters
- x / The train Method
- y / The train Method
- form / The train Method
- data / The train Method
- weights / The train Method
- subset / The train Method
- method / The train Method
- TraMineR
- used, for determining sequences / Determining sequences using TraMineR
- usage / Usage
- example / Determining sequences in training and careers
- TraMineR, datasets
- ts function, parameters
- data / Time series
- start / Time series
- end / Time series
- frequency / Time series
- deltat / Time series
- ts.eps / Time series
- class / Time series
- names / Time series
- TTR package
- about / Automatic forecasting packages
- SMA function / The SMA function
- turbulence
U
- unsupervised learning
- about / Unsupervised learning
- unsupervised learning, techniques
- cluster analysis / Cluster analysis
- density estimation / Density estimation
- expectation-maximization (EM) / Expectation-maximization
- hidden Markov models (HMM) / Hidden Markov models
- blind signal separation / Blind signal separation
V
- vector quantization
- about / Density estimation
- VectorSource
- using / Using VectorSource
- vegan package
- about / Packages
- VEV
- about / Example
- vrmlgenbar3D
- about / vrmlgenbar3D
- vrmlgen package
- about / Packages
W
- wine quality data, UCI Machine Learning Repository
- URL / Example
- word cloud
- generating / Word graphics
- about / Word cloud
- word graphics
- about / Word graphics
- word stems
- about / Word stems
- world map
- points, plotting on / Plotting points on a world map
X
- XML package
- about / Packages
- XML text
- analyzing / Analyzing the XML text