cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/r5a-9vm-r6n
title: Microlicia phlogiformis (DC.) Versiane & R. Romero

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.25625/who995/9tbgky
title: FFT_Peaks_12A_340K.txt

description: :unav
DOI: 10.3535/bl1-eb0-m08
title: Miconia leafluminensis R. Goldenb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dgh-fvw-rqs
title: Dichanthelium viscidellum (Scribn.) Gould

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.6084/m9.figshare.29269838
title: Fractional Cross-Validation for Optimizing Hyperparameters of Supervised Learning Algorithms

description: K-fold cross-validation (CV) is a robust method for estimating generalization performance of supervised learning models. Although CV is more reliable than using a single hold-out test set, it is also more computationally expensive since the model must be fit K times. This can be prohibitive when optimizing the hyperparameters, since this involves conducting K-fold CV repeatedly at many hyperparameter configurations. In this work, we propose a highly-efficient Bayesian optimization algorithm for optimizing the hyperparameters of supervised learning algorithms with K-fold CV error as the evaluation criterion. Our approach exploits the fact that the single-fold out-of-sample error is pairwise correlated across different hyperparameter configurations. We introduce a hierarchical Gaussian process model that is well-suited to accommodate this inherent correlation structure across folds and across the hyperparameter space. Our resulting algorithm requires evaluating only a single fold for many hyperparameter configurations, enabling us to efficiently find the optimal hyperparameters. We refer to this as “fractional CV”, since it requires only a small fraction of the folds to be evaluated, relative to what is required for full K-fold CV. We demonstrate the efficacy of our method on a number of models and real datasets.
DOI: 10.25625/who995/nrx3hb
title: FFT_16A_320K.txt

description: :unav
DOI: 10.3535/16l-xk4-lr8
title: Urochloa brizantha (A.Rich.) R.D.Webster

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vx3-fmf-aeh
title: Miconia sellowiana Naudin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.6084/m9.figshare.29269838.v2
title: Fractional Cross-Validation for Optimizing Hyperparameters of Supervised Learning Algorithms

description: K-fold cross-validation (CV) is a robust method for estimating generalization performance of supervised learning models. Although CV is more reliable than using a single hold-out test set, it is also more computationally expensive since the model must be fit K times. This can be prohibitive when optimizing the hyperparameters, since this involves conducting K-fold CV repeatedly at many hyperparameter configurations. In this work, we propose a highly-efficient Bayesian optimization algorithm for optimizing the hyperparameters of supervised learning algorithms with K-fold CV error as the evaluation criterion. Our approach exploits the fact that the single-fold out-of-sample error is pairwise correlated across different hyperparameter configurations. We introduce a hierarchical Gaussian process model that is well-suited to accommodate this inherent correlation structure across folds and across the hyperparameter space. Our resulting algorithm requires evaluating only a single fold for many hyperparameter configurations, enabling us to efficiently find the optimal hyperparameters. We refer to this as “fractional CV”, since it requires only a small fraction of the folds to be evaluated, relative to what is required for full K-fold CV. We demonstrate the efficacy of our method on a number of models and real datasets.
DOI: 10.25625/who995/ypgln1
title: FFT_12A_260K.txt

description: :unav
DOI: 10.3535/9yz-fdg-zxc
title: Cordylostigma longifolium (Klotzsch) Groeninckx & Dessein

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/rdd-s2e-ttm
title: Miconia ligustroides (DC.) Naudin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.6084/m9.figshare.29269838.v1
title: Fractional cross-validation for optimizing hyperparameters of supervised learning algorithms

description: K-fold cross-validation (CV) is a robust method for estimating generalization performance of supervised learning models. Although CV is more reliable than using a single hold-out test set, it is also more computationally expensive since the model must be fit K times. This can be prohibitive when optimizing the hyperparameters, since this involves conducting K-fold CV repeatedly at many hyperparameter configurations. In this work, we propose a highly-efficient Bayesian optimization algorithm for optimizing the hyperparameters of supervised learning algorithms with K-fold CV error as the evaluation criterion. Our approach exploits the fact that the single-fold out-of-sample error is pairwise correlated across different hyperparameter configurations. We introduce a hierarchical Gaussian process model that is well-suited to accommodate this inherent correlation structure across folds and across the hyperparameter space. Our resulting algorithm requires evaluating only a single fold for many hyperparameter configurations, enabling us to efficiently find the optimal hyperparameters. We refer to this as “fractional CV”, since it requires only a small fraction of the folds to be evaluated, relative to what is required for full K-fold CV. We demonstrate the efficacy of our method on a number of models and real datasets.
DOI: 10.25625/who995/qwzoya
title: FFT_Peaks_18A_370K.txt

description: :unav
DOI: 10.25625/who995/wcw2sw
title: FFT_26A_300K.txt

description: :unav
DOI: 10.3535/8dl-g3k-sjt
title: Hypericum scabrum L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/x2w-ka7-5tw
title: Pleroma clavatum (Pers.) P. J. F. Guim. & Michelang.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.25625/who995/nydvba
title: FFT_8A_350K.txt

description: :unav
DOI: 10.3535/22k-ylv-h6n
title: Pombalia atropurpurea (A. St.-Hil.) Paula-Souza

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8cs-jeh-fvc
title: Miconia minutiflora (Bonpl.) DC.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.25625/who995/gqbuue
title: FFT_28A_310K.txt

description: :unav
DOI: 10.3535/2el-maf-wwy
title: Miconia ligustroides (DC.) Naudin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/re0-jvx-5wt
title: Miconia sellowiana Naudin

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.25625/who995/dpmhgd
title: FFT_24A_310K.txt

description: :unav
DOI: 10.25625/who995/z2jxjr
title: FFT_8A_275K.txt

description: :unav
DOI: 10.3535/8hd-rqk-4tp
title: Kielmeyera variabilis Mart.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/9s9-30v-zyr
title: Poa bulbosa L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.25625/who995/pqevck
title: FFT_14A_305K.txt

description: :unav
DOI: 10.3535/nyn-0f7-6qt
title: Urochloa oligotricha (Fig. & De Not.) Henrard

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.25625/who995/gqctij
title: FFT_6A_340K.txt

description: :unav
DOI: 10.15468/dl.q8bujr
title: Occurrence Download

description: A dataset containing 332 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is El Salvador",
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is Eumomota P.L.Sclater, 1858"
 ]
}

 The dataset includes 332 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007332-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n95k78
title: Occurrence Download

description: A dataset containing 260 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Material citation, Specimen)",
 "Country is one of (Panama, Costa Rica)",
 "OccurrenceStatus is Present",
 "TaxonKey is Pharomachrus mocinno La Llave, 1832"
 ]
}

 The dataset includes 260 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007331-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1387289.10fu
title: SH1387289.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1387290.10fu
title: SH1387290.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1387292.10fu
title: SH1387292.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1387294.10fu
title: SH1387294.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1387295.10fu
title: SH1387295.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.ku5yzs
title: Occurrence Download

description: A dataset containing 1094528 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fraxinus angustifolia, Fraxinus australis, Fraxinus dimorpha, Fraxinus excelsior, Fraxinus ornus, Fraxinus oxyphylla, Fraxinus pallisiae)",
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (INTRODUCED)"
 ]
 }
 },
 "Geometry POLYGON ((-20.00014 -37.000139, 62.99986 -37.000139, 62.99986 54.999861, -20.00014 54.999861, -20.00014 -37.000139))"
 ]
}

 The dataset includes 1094528 records from 3463 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005868-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3vfae
title: Occurrence Download

description: A dataset containing 3207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyanocorax beecheii (Vigors, 1829))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3207 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005402-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z42q6v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phlomis ×rechingeri Hub.-Mor."
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074884-230530130749713/datasets/export for details.
DOI: 10.15468/dl.kz2w5e
title: Occurrence Download

description: A dataset containing 856 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Rhagologus leucostigma (Salvadori, 1876))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 856 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011514-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rpvw98
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cylindrospermopsis raciborskii (Wołosz.) Seenayya & Subbaraju"
 ]
}

 The dataset includes 119 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004222-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.crzzuh
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Stachys pseudophlomis C.Y.Wu"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005387-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f4md3r
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phlomis ×semiorbata Rech.f."
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074895-230530130749713/datasets/export for details.
DOI: 10.15468/dl.fuagfs
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ianthocincla konkakinhensis (J.C.Eames & C.Eames, 2001))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011515-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g5z2mt
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Agalmyla stenosiphon Hilliard & B.L.Burtt"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004215-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7bb6f
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phlomis regelii Popov"
 ]
}

 The dataset includes 19 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074885-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mz4tfj
title: Occurrence Download

description: A dataset containing 15960 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Larosterna inca (R.Lesson & Garnot, 1827))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 15960 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005403-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6pswz4
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-103.64494 20.24861,-102.80296 20.24861,-102.80296 21.06806,-103.64494 21.06806,-103.64494 20.24861))",
 "TaxonKey is one of (Andrenidae, Melittidae)"
 ]
}

 The dataset includes 25 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011518-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fgs26k
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Agalmyla tamrauana Hilliard & B.L.Burtt"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004216-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vss7yq
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phlomis sewerzowii Regel"
 ]
}

 The dataset includes 16 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074898-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x4dahd
title: Occurrence Download

description: A dataset containing 101 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Colinus leucopogon (R.Lesson, 1842))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 101 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005415-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yekxuf
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Agalmyla tobensis Hilliard & B.L.Burtt"
 ]
}

 The dataset includes 17 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004217-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nfasa5
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Allium hirtovaginum Candargy"
 ]
}

 The dataset includes 40 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011524-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.