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scikit fda map
Carlos Ramos Carreño edited this page Apr 29, 2019
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Map of the status of the features in scikit-fda:
custom_mark10 digraph G { skfda -> types skfda -> preprocessing skfda -> datasets skfda -> clustering skfda -> regression skfda -> classification skfda -> "dimensionality reduction" skfda -> visualization skfda -> depth skfda -> metrics skfda -> outliers
dense [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.grid.FDataGrid.html#skfda.grid.FDataGrid"]
types -> dense
types -> incomplete
incomplete -> sparse
incomplete -> longitudinal
basis [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.FDataBasis.html#skfda.FDataBasis"]
types -> basis
Fourier [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.basis.Fourier.html#skfda.basis.Fourier"]
basis -> Fourier
BSpline [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.basis.BSpline.html#skfda.basis.BSpline"]
basis -> BSpline
monomial [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.basis.Monomial.html#skfda.basis.Monomial"]
basis -> monomial
basis -> wavelet
preprocessing -> derivatives
"symmetric difference" [style=filled,color=lightgrey,label="symmetric difference (derivative method, 1d)"]
derivatives -> "symmetric difference"
preprocessing -> registration
"shift registration" [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.registration.shift_registration.html#skfda.registration.shift_registration"]
registration -> "shift registration"
"landmark shift" [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.registration.landmark_shift.html#skfda.registration.landmark_shift"]
registration -> "landmark shift"
"landmark registration" [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.registration.landmark_registration.html#skfda.registration.landmark_registration"]
registration -> "landmark registration"
"elastic registration" [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.registration.elastic_registration.html#skfda.registration.elastic_registration"]
registration -> "elastic registration"
"MSE decomposition" [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.registration.mse_decomposition.html#skfda.registration.mse_decomposition"]
registration -> "MSE decomposition"
preprocessing -> smoothing
FM [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.depth_measures.fraiman_muniz_depth.html#skfda.depth_measures.fraiman_muniz_depth"]
depth -> FM
BD [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.depth_measures.band_depth.html#skfda.depth_measures.band_depth"]
depth -> BD
MBD [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.depth_measures.modified_band_depth.html#skfda.depth_measures.modified_band_depth"]
depth -> MBD
depth -> "h-mode"
depth -> "random projections"
depth -> median
boxplot [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/fdata_boxplot.html"]
depth -> boxplot
depth -> "depth outliers"
depth -> "DD plot"
"dimensionality reduction" -> projection
"dimensionality reduction" -> "variable selection"
projection -> FPCA
projection -> FPLS
"variable selection" -> RKHS
"variable selection" -> MH
"variable selection" -> RMH
"variable selection" -> mRMR
"variable selection" -> wrapper
wrapper -> Fwd
wrapper -> Bwd
Lp [style=filled,color=lightgrey,URL="https://fda.readthedocs.io/en/latest/modules/autosummary/skfda.metrics.lp_distance.html#skfda.metrics.lp_distance"]
metrics -> Lp
Linf [label="L∞"]
metrics -> Linf
outliers -> "MS plot"
outliers -> outliergram
visualization -> boxplot
visualization -> "DD plot"
visualization -> "MS plot"
visualization -> outliergram
} custom_mark10