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|[fda.bsignal](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.bsignal)| B-spline Feature Extraction|[tf](https://cran.r-project.org/package=tf), [mboost](https://cran.r-project.org/package=mboost), [FDboost](https://cran.r-project.org/package=FDboost)| fda, data transform |
117
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|[fda.cor](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.cor)| Cross-Correlation of Functional Data |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
118
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|[fda.extract](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.extract)| Extracts Simple Features from Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
119
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|[fda.flatten](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.flatten)| Flattens Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
120
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|[fda.fourier](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.fourier)| Fast Fourier transform features |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
121
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|[fda.fpca](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.fpca)| Functional Principal Component Analysis |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
122
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|[fda.interpol](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.interpol)| Interpolate Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
123
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|[fda.random_effect](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.random_effect)| Extracts Random Effects from Functional Columns |[tf](https://cran.r-project.org/package=tf), [lme4](https://cran.r-project.org/package=lme4)| fda, data transform |
124
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|[fda.scalerange](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.scalerange)| Linearly Transform the Domain of Functional Data |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
125
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|[fda.smooth](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.smooth)| Smoothing Functional Columns |[tf](https://cran.r-project.org/package=tf), stats| fda, data transform |
126
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|[fda.tsfeats](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.tsfeats)| Time Series Feature Extraction |[tf](https://cran.r-project.org/package=tf), [tsfeatures](https://cran.r-project.org/package=tsfeatures)| fda, data transform |
127
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|[fda.wavelets](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.wavelets)| Discrete Wavelet transform features |[tf](https://cran.r-project.org/package=tf), [wavelets](https://cran.r-project.org/package=wavelets)| fda, data transform |
128
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|[fda.zoom](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.zoom)| Zoom In/Out on Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
|[fda.cor](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.cor)| Cross-Correlation of Functional Data |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
124
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|[fda.extract](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.extract)| Extracts Simple Features from Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
125
+
|[fda.flatten](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.flatten)| Flattens Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
126
+
|[fda.fourier](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.fourier)| Fast Fourier transform features |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
127
+
|[fda.fpca](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.fpca)| Functional Principal Component Analysis |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
128
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|[fda.interpol](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.interpol)| Interpolate Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
129
+
|[fda.random_effect](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.random_effect)| Extracts Random Effects from Functional Columns |[tf](https://cran.r-project.org/package=tf), [lme4](https://cran.r-project.org/package=lme4)| fda, data transform |
130
+
|[fda.scalerange](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.scalerange)| Linearly Transform the Domain of Functional Data |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
|[fda.tsfeats](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.tsfeats)| Time Series Feature Extraction |[tf](https://cran.r-project.org/package=tf), [tsfeatures](https://cran.r-project.org/package=tsfeatures)| fda, data transform |
133
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|[fda.wavelets](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.wavelets)| Discrete Wavelet transform features |[tf](https://cran.r-project.org/package=tf), [wavelets](https://cran.r-project.org/package=wavelets)| fda, data transform |
134
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|[fda.zoom](https://mlr3fda.mlr-org.com/dev/reference/mlr_pipeops_fda.zoom)| Zoom In/Out on Functional Columns |[tf](https://cran.r-project.org/package=tf)| fda, data transform |
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