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opt · optimization
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API reference
classes
AdamOptimizer
GradientDescent
MomentumOptimizer
RMSProp
functions
adam
adamStep
backtrackingLineSearch
createOptimizer
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minimize
minimizeScalar
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numericalGradient
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rmsprop
rmspropStep
rootScalar
solve
strongWolfeLineSearch
variables
default
proba · probability
Overview
API reference
@tangent.to
namespaces
special
functions
betainc
betaincInv
digamma
erf
erfc
gammainc
gammaincc
gammaincInv
lbeta
lchoose
lgamma
normalCdf
normalQuantile
special
functions
createRng
variables
bernoulli
beta
binomial
chi2
default
distributions
exponential
f
gamma
halfnormal
lognormal
normal
poisson
studentT
uniform
lina · linear algebra
Overview
API reference
functions
cholesky
choleskySolve
cond
det
diag
eigSym
eigSymGeneralized
identity
inv
invSqrtSym
isPositiveDefinite
lstsq
lu
luFactor
luFactorSolve
matmul
norm
pinv
pinvSolve
qr
rank
solve
svd
trace
transpose
variables
default
grad · automatic differentiation
Overview
API reference
classes
Var
functions
addDiag
asTensor
cholesky
compile
compileFromJSON
concat
diagPart
dot
eye
grad
inv
isTensor
jacobian
logdetPSD
matmul
mean
pow
reshape
slice
solveGeneral
solvePSD
splitValueAndGrad
sum
tensor
toNested
trace
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triangularSolve
valueAndGrad
valueAndGradFns
variable
zeros
variables
add
div
exp
lgamma
log
maximum
minimum
mul
neg
relu
sigmoid
sqrt
square
sub
tanh
ode · differential equations
Overview
API reference
functions
euler
rk2
rk4
rk45
rosenbrock
solve
variables
default
Applications
ds · data science
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API reference
@tangent.to
namespaces
core
functions
applyFormula
parseFormula
namespaces
linalg
classes
Matrix
SingularValueDecomposition
functions
cholesky
choleskySolve
covarianceMatrix
eig
eigGeneralized
inverse
mmul
pseudoInverse
solve
solveLeastSquares
svd
symmetricInverseSqrt
toMatrix
transpose
linalg
math
functions
approxEqual
extent
guardFinite
guardPositive
guardProbability
max
mean
median
min
percentile
quantile
range
stddev
sum
summaryQuantiles
variance
variables
E
EPSILON
PI
sd
std
math
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optimize
persistence
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KDTree
functions
buildKDTree
spatial
table
classes
LabelEncoder
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applyColumns
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oneHotEncodeTable
prepareX
prepareXY
select
toColumns
toMatrix
toVector
table
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BranchPipeline
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LocalOutlierFactor
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Matern
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Periodic
Pipeline
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Recipe
SimpleImputer
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recipe
simpleImpute
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classificationError
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mse
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dbscan
functions
fit
predict
dbscan
distances
functions
canberra
chebyshev
cosine
createGowerDistance
euclidean
getDistanceFunction
gower
hamming
manhattan
minkowski
distances
hca
functions
cut
cutHeight
fit
hca
interpret
functions
coefficientImportance
correlationMatrix
featureImportance
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partialDependence
residualPlotData
interpret
kmeans
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fit
predict
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functions
crossEntropy
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huberLoss
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mseLoss
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metrics
functions
accuracy
adjustedRandIndex
cohenKappa
confusionMatrix
confusionMatrixText
f1
logLoss
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mse
precision
r2
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rmse
rocAuc
metrics
ml
explain
classes
KernelExplainer
PermutationExplainer
TreeExplainer
functions
importanceData
kernelShap
summaryData
treeShap
ml/explain
polynomial
functions
fit
polynomialFeatures
predict
polynomial
preprocessing
classes
LabelEncoder
MinMaxScaler
OneHotEncoder
PolynomialFeatures
StandardScaler
functions
cleanCategorical
fitPreprocessor
labelEncode
parseNumeric
preprocess
transformWithPipeline
variables
preprocessCategorical
preprocessing
silhouette
functions
silhouetteByCluster
silhouetteSamples
silhouette
tuning
functions
GridSearchCV
RandomSearchCV
variables
distributions
tuning
utils
functions
random
randomInt
sample
setSeed
shuffle
utils
validation
functions
crossValidate
groupKFold
kFold
leaveOneOut
shuffleSplit
stratifiedKFold
trainTestSplit
validation
ml
mva
classes
CCA
LDA
PCA
RDA
namespaces
cca
functions
fit
transform
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transformY
cca
composition
classes
CompositionalImputer
CompositionalOutlierDetector
functions
alr
alrInv
center
closure
clr
clrInv
compositionalOutliers
ilr
ilrInv
imputeMissing
inner
multiplicativeReplacement
power
sbpBasis
variables
centralize
composition
lda
functions
fit
predict
transform
lda
pca
functions
cumulativeVariance
fit
transform
pca
rda
functions
fit
permutationTest
transform
rda
mva
plot
functions
createD3DendrogramRenderer
dendrogramLayout
diagnosticDashboard
effectPlot
ordiplot
partialResidualPlot
plotCalibration
plotClusterMembership
plotClusterStability
plotCondensedTree
plotConfusionMatrix
plotCorrelationMatrix
plotFeatureImportance
plotHCA
plotHDBSCAN
plotHDBSCANDashboard
plotHDBSCANDendrogram
plotLearningCurve
plotPartialDependence
plotPrecisionRecall
plotQQ
plotResiduals
plotROC
plotScree
plotSilhouette
qqPlot
residualPlot
residualsLeveragePlot
resolveGroupValues
scaleLocationPlot
plot
stats
classes
ChiSquareTest
GLM
OneSampleTTest
OneWayAnova
TukeyHSD
TwoSampleTTest
functions
aicWeightPlot
bonferroni
coefficientComparisonPlot
cohensD
compareModels
crossValidate
crossValidateModels
etaSquared
fdr
fisherExactTest
holmBonferroni
leveneTest
likelihoodRatioTest
modelSelectionPlot
omegaSquared
pairwiseLRT
pearsonCorrelation
qchisq
spearmanCorrelation
variables
beta
chisq
gamma
hypothesis
normal
uniform
stats
variables
default
mc · Bayesian inference
Overview
API reference
classes
Bernoulli
Beta
Distribution
Exponential
Gamma
HalfNormal
HamiltonianMC
HMC
Lognormal
MetropolisHastings
Model
Normal
NUTS
Poisson
StudentT
Uniform
functions
autocorrPlot
effectiveSampleSize
ess
forestPlot
gelmanRubin
getRng
pairPlot
posteriorPlot
printSummary
rankPlot
rhat
runChain
sampleChains
setRandomSeed
summarize
summary
tracePlot
traceToCSV
traceToJSON
variables
default
diagnostics
distributions
ops
plot
samplers
nn · neural networks
Overview
API reference
sem · structural equation modeling
Overview
API reference
functions
buildModel
parseModel
sampleCov
sem
variables
cfa
default
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transpose
transpose
(
aIn
):
Var
Defined in:
ops.js:605
Matrix transpose.
Parameters
aIn
any
Returns
Var
