Man pages for daltoolbox
Leveraging Experiment Lines to Data Analytics

actionAction
action.dal_transformAction implementation for transform
adjust_class_labelAdjust categorical mapping
adjust_data.frameAdjust to data frame
adjust_factorAdjust factors
adjust_matrixAdjust to matrix
adjust_ts_dataAdjust 'ts_data'
autoenc_encodeAutoencoder - Encode
autoenc_encode_decodeAutoencoder - Encode-decode
BostonBoston Housing Data (Regression)
categ_mappingCategorical mapping
cla_dtreeDecision Tree for classification
cla_knnK Nearest Neighbor Classification
cla_majorityMajority Classification
cla_mlpMLP for classification
cla_nbNaive Bayes Classifier
cla_rfRandom Forest for classification
classificationclassification
cla_svmSVM for classification
cla_tuneClassification Tune
clusterCluster
cluster_dbscanDBSCAN
clustererClusterer
cluster_kmeansk-means
cluster_pamPAM
clu_tuneClustering Tune
dal_baseClass dal_base
dal_learnerDAL Learner
dal_transformDAL Transform
dal_tuneDAL Tune
data_sampleData Sample
do_fitFit Time Series Model
do_predictPredict Time Series Model
dt_pcaPCA
evaluateEvaluate
fitFit
fit.cla_tunetune hyperparameters of ml model
fit.cluster_dbscanfit dbscan model
fit_curvature_maxmaximum curvature analysis
fit_curvature_minminimum curvature analysis
inverse_transformInverse Transform
k_foldK-fold sampling
minmaxMin-max normalization
MSE.tsMSE
outliersOutliers
plot_barPlot bar graph
plot_boxplotPlot boxplot
plot_boxplot_classBoxplot per class
plot_densityPlot density
plot_density_classPlot density per class
plot_groupedbarPlot grouped bar
plot_histPlot histogram
plot_lollipopPlot lollipop
plot_pieplotPlot pie
plot_pointsPlot points
plot_radarPlot radar
plot_scatterScatter graph
plot_seriesPlot series
plot_stackedbarPlot stacked bar
plot_tsPlot time series chart
plot_ts_predPlot a time series chart with predictions
predictorDAL Predict
R2.tsR2
reg_dtreeDecision Tree for regression
reg_knnknn regression
reg_mlpMLP for regression
regressionRegression
reg_rfRandom Forest for regression
reg_svmSVM for regression
reg_tuneRegression Tune
sample_randomSample Random
sample_stratifiedStratified Random Sampling
select_hyperSelection hyper parameters
select_hyper.cla_tuneselection of hyperparameters
select_hyper.ts_tuneSelect Optimal Hyperparameters for Time Series Models
set_paramsAssign parameters
set_params.defaultDefault Assign parameters
sin_dataTime series example dataset
sMAPE.tssMAPE
smoothingSmoothing
smoothing_clusterSmoothing by cluster
smoothing_freqSmoothing by Freq
smoothing_interSmoothing by interval
sub-.ts_dataSubset Extraction for Time Series Data
train_testTrain-Test Partition
train_test_from_foldsk-fold training and test partition object
transformTransform
ts_arimaARIMA
ts_conv1dConv1D
ts_datats_data
ts_elmELM
ts_headExtract the First Observations from a 'ts_data' Object
ts_knnKNN time series prediction
ts_lstmLSTM
ts_mlpMLP
ts_norm_anTime Series Adaptive Normalization
ts_norm_diffTime Series Diff
ts_norm_eanTime Series Adaptive Normalization (Exponential Moving...
ts_norm_gminmaxTime Series Global Min-Max
ts_norm_swminmaxTime Series Sliding Window Min-Max
ts_projectionTime Series Projection
ts_regTSReg
ts_regswTSRegSW
ts_rfRandom Forest
ts_sampleTime Series Sample
ts_svmSVM
ts_tuneTime Series Tune
zscoreZ-score normalization
daltoolbox documentation built on Nov. 3, 2024, 9:06 a.m.