Estimating Class Proportions in Boar Semen Analysis Using the Hellinger Distance View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Víctor González-Castro , Rocío Alaiz-Rodríguez , Laura Fernández-Robles , R. Guzmán-Martínez , Enrique Alegre

ABSTRACT

Advances in image analysis make possible the automatic semen analysis in the veterinary practice. The proportion of sperm cells with damaged/intact acrosome, a major aspect in this assessment, depends strongly on several factors, including animal diversity and manipulation/conservation conditions. For this reason, the class proportions have to be quantified for every future (test) semen sample. In this work, we evaluate quantification approaches based on the confusion matrix, the posterior probability estimates and a novel proposal based on the Hellinger distance. Our information theoretic-based approach to estimate the class proportions measures the similarity between several artificially generated calibration distributions and the test one at different stages: the data distributions and the classifier output distributions. Experimental results show that quantification can be conducted with a Mean Absolute Error below 0.02, what seems promising in this field. More... »

PAGES

284-293

References to SciGraph publications

  • 2008-10. Quantifying counts and costs via classification in DATA MINING AND KNOWLEDGE DISCOVERY
  • 2009-01. A framework for monitoring classifiers’ performance: when and why failure occurs? in KNOWLEDGE AND INFORMATION SYSTEMS
  • Book

    TITLE

    Trends in Applied Intelligent Systems

    ISBN

    978-3-642-13021-2
    978-3-642-13022-9

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-13022-9_29

    DOI

    http://dx.doi.org/10.1007/978-3-642-13022-9_29

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1009948306


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Statistics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Dpto. de Ingenier\u00eda El\u00e9ctrica y de Sistemas"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Gonz\u00e1lez-Castro", 
            "givenName": "V\u00edctor", 
            "id": "sg:person.010551001361.75", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010551001361.75"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Dpto. de Ingenier\u00eda El\u00e9ctrica y de Sistemas"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Alaiz-Rodr\u00edguez", 
            "givenName": "Roc\u00edo", 
            "id": "sg:person.07453503162.70", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07453503162.70"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Dpto. de Ingenier\u00eda El\u00e9ctrica y de Sistemas"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fern\u00e1ndez-Robles", 
            "givenName": "Laura", 
            "id": "sg:person.010415303037.45", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010415303037.45"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Leon", 
              "id": "https://www.grid.ac/institutes/grid.4807.b", 
              "name": [
                "Servicio de Informatica y Comunicaciones, University of Le\u00f3n, Campus de Vegazana s/n, 24071, Le\u00f3n, Spain"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Guzm\u00e1n-Mart\u00ednez", 
            "givenName": "R.", 
            "id": "sg:person.012606537631.25", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012606537631.25"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Dpto. de Ingenier\u00eda El\u00e9ctrica y de Sistemas"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Alegre", 
            "givenName": "Enrique", 
            "id": "sg:person.016266057305.75", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016266057305.75"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s10115-008-0139-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002914135", 
              "https://doi.org/10.1007/s10115-008-0139-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10115-008-0139-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002914135", 
              "https://doi.org/10.1007/s10115-008-0139-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1162/089976602753284446", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005903963"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10618-008-0097-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013037105", 
              "https://doi.org/10.1007/s10618-008-0097-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10618-008-0097-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013037105", 
              "https://doi.org/10.1007/s10618-008-0097-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1145/1557019.1557117", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040178318"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0167-8655(02)00390-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041018891"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.patcog.2008.01.025", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042374125"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1561/0100000004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068000263"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3115/1220175.1220187", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1099221938"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3115/1220175.1220187", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1099221938"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2010", 
        "datePublishedReg": "2010-01-01", 
        "description": "Advances in image analysis make possible the automatic semen analysis in the veterinary practice. The proportion of sperm cells with damaged/intact acrosome, a major aspect in this assessment, depends strongly on several factors, including animal diversity and manipulation/conservation conditions. For this reason, the class proportions have to be quantified for every future (test) semen sample. In this work, we evaluate quantification approaches based on the confusion matrix, the posterior probability estimates and a novel proposal based on the Hellinger distance. Our information theoretic-based approach to estimate the class proportions measures the similarity between several artificially generated calibration distributions and the test one at different stages: the data distributions and the classifier output distributions. Experimental results show that quantification can be conducted with a Mean Absolute Error below 0.02, what seems promising in this field.", 
        "editor": [
          {
            "familyName": "Garc\u00eda-Pedrajas", 
            "givenName": "Nicol\u00e1s", 
            "type": "Person"
          }, 
          {
            "familyName": "Herrera", 
            "givenName": "Francisco", 
            "type": "Person"
          }, 
          {
            "familyName": "Fyfe", 
            "givenName": "Colin", 
            "type": "Person"
          }, 
          {
            "familyName": "Ben\u00edtez", 
            "givenName": "Jos\u00e9 Manuel", 
            "type": "Person"
          }, 
          {
            "familyName": "Ali", 
            "givenName": "Moonis", 
            "type": "Person"
          }
        ], 
        "genre": "chapter", 
        "id": "sg:pub.10.1007/978-3-642-13022-9_29", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": {
          "isbn": [
            "978-3-642-13021-2", 
            "978-3-642-13022-9"
          ], 
          "name": "Trends in Applied Intelligent Systems", 
          "type": "Book"
        }, 
        "name": "Estimating Class Proportions in Boar Semen Analysis Using the Hellinger Distance", 
        "pagination": "284-293", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1009948306"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/978-3-642-13022-9_29"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "2f649aea66502989f8ba58a33f11f215eec54f0ef6bed8a2ffb2591167581d2a"
            ]
          }
        ], 
        "publisher": {
          "location": "Berlin, Heidelberg", 
          "name": "Springer Berlin Heidelberg", 
          "type": "Organisation"
        }, 
        "sameAs": [
          "https://doi.org/10.1007/978-3-642-13022-9_29", 
          "https://app.dimensions.ai/details/publication/pub.1009948306"
        ], 
        "sdDataset": "chapters", 
        "sdDatePublished": "2019-04-16T08:37", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000365_0000000365/records_71698_00000000.jsonl", 
        "type": "Chapter", 
        "url": "https://link.springer.com/10.1007%2F978-3-642-13022-9_29"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-13022-9_29'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-13022-9_29'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-13022-9_29'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-13022-9_29'


     

    This table displays all metadata directly associated to this object as RDF triples.

    147 TRIPLES      23 PREDICATES      35 URIs      20 LITERALS      8 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/978-3-642-13022-9_29 schema:about anzsrc-for:01
    2 anzsrc-for:0104
    3 schema:author Na52d36d091a940bbb4bf1eef211c9438
    4 schema:citation sg:pub.10.1007/s10115-008-0139-1
    5 sg:pub.10.1007/s10618-008-0097-y
    6 https://doi.org/10.1016/j.patcog.2008.01.025
    7 https://doi.org/10.1016/s0167-8655(02)00390-2
    8 https://doi.org/10.1145/1557019.1557117
    9 https://doi.org/10.1162/089976602753284446
    10 https://doi.org/10.1561/0100000004
    11 https://doi.org/10.3115/1220175.1220187
    12 schema:datePublished 2010
    13 schema:datePublishedReg 2010-01-01
    14 schema:description Advances in image analysis make possible the automatic semen analysis in the veterinary practice. The proportion of sperm cells with damaged/intact acrosome, a major aspect in this assessment, depends strongly on several factors, including animal diversity and manipulation/conservation conditions. For this reason, the class proportions have to be quantified for every future (test) semen sample. In this work, we evaluate quantification approaches based on the confusion matrix, the posterior probability estimates and a novel proposal based on the Hellinger distance. Our information theoretic-based approach to estimate the class proportions measures the similarity between several artificially generated calibration distributions and the test one at different stages: the data distributions and the classifier output distributions. Experimental results show that quantification can be conducted with a Mean Absolute Error below 0.02, what seems promising in this field.
    15 schema:editor N0cee368db36b4f39b702f5a82d17ce48
    16 schema:genre chapter
    17 schema:inLanguage en
    18 schema:isAccessibleForFree false
    19 schema:isPartOf N9e6807f48ddc4d7ea2c39fc6bf81716a
    20 schema:name Estimating Class Proportions in Boar Semen Analysis Using the Hellinger Distance
    21 schema:pagination 284-293
    22 schema:productId N019bd095a83d40a7baf1ca43fb3d94f3
    23 N43f7f925d813416cb9b5686beba23c10
    24 Nba7d72ad353b4c01a48889c7de21e62a
    25 schema:publisher N1528981d50c443db92800e9e07256e66
    26 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009948306
    27 https://doi.org/10.1007/978-3-642-13022-9_29
    28 schema:sdDatePublished 2019-04-16T08:37
    29 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    30 schema:sdPublisher N922e42ff68494d27ab8e0589c1dface5
    31 schema:url https://link.springer.com/10.1007%2F978-3-642-13022-9_29
    32 sgo:license sg:explorer/license/
    33 sgo:sdDataset chapters
    34 rdf:type schema:Chapter
    35 N019bd095a83d40a7baf1ca43fb3d94f3 schema:name doi
    36 schema:value 10.1007/978-3-642-13022-9_29
    37 rdf:type schema:PropertyValue
    38 N0cee368db36b4f39b702f5a82d17ce48 rdf:first N4228fc765f6b472f8ce64dc25f1fc30f
    39 rdf:rest Nc6103e1b4364447dbbf1e60463363e86
    40 N1528981d50c443db92800e9e07256e66 schema:location Berlin, Heidelberg
    41 schema:name Springer Berlin Heidelberg
    42 rdf:type schema:Organisation
    43 N19fee603b41847dc94501094930a27ea rdf:first N60558565a8874bb69bcb1a3b13448972
    44 rdf:rest N76be6334fdfe4295830519963ea6467b
    45 N3e326cf9a5cf4c37b1d282f4475b7c09 schema:name Dpto. de Ingeniería Eléctrica y de Sistemas
    46 rdf:type schema:Organization
    47 N4026f94e02314299ac79cc38f9366304 schema:name Dpto. de Ingeniería Eléctrica y de Sistemas
    48 rdf:type schema:Organization
    49 N4228fc765f6b472f8ce64dc25f1fc30f schema:familyName García-Pedrajas
    50 schema:givenName Nicolás
    51 rdf:type schema:Person
    52 N43f7f925d813416cb9b5686beba23c10 schema:name readcube_id
    53 schema:value 2f649aea66502989f8ba58a33f11f215eec54f0ef6bed8a2ffb2591167581d2a
    54 rdf:type schema:PropertyValue
    55 N4869b7d3adbf49ec93eac85ed8464061 rdf:first sg:person.010415303037.45
    56 rdf:rest Naba7ce3edfdf4d7f9228f06b8d7450d0
    57 N543c448abb3842dcba7426226675eaa5 rdf:first sg:person.016266057305.75
    58 rdf:rest rdf:nil
    59 N60558565a8874bb69bcb1a3b13448972 schema:familyName Fyfe
    60 schema:givenName Colin
    61 rdf:type schema:Person
    62 N76be6334fdfe4295830519963ea6467b rdf:first N7e0a74d886be4e019dbe88ae76fc8ec6
    63 rdf:rest Neb299f7d262f4d12b5e2e1eb33f74562
    64 N7c6cd8084175445baca47f1fe5092739 schema:name Dpto. de Ingeniería Eléctrica y de Sistemas
    65 rdf:type schema:Organization
    66 N7e0a74d886be4e019dbe88ae76fc8ec6 schema:familyName Benítez
    67 schema:givenName José Manuel
    68 rdf:type schema:Person
    69 N922e42ff68494d27ab8e0589c1dface5 schema:name Springer Nature - SN SciGraph project
    70 rdf:type schema:Organization
    71 N9e6807f48ddc4d7ea2c39fc6bf81716a schema:isbn 978-3-642-13021-2
    72 978-3-642-13022-9
    73 schema:name Trends in Applied Intelligent Systems
    74 rdf:type schema:Book
    75 Na52d36d091a940bbb4bf1eef211c9438 rdf:first sg:person.010551001361.75
    76 rdf:rest Nc64007dd6266406e92bdcc279e7a1660
    77 Naba7ce3edfdf4d7f9228f06b8d7450d0 rdf:first sg:person.012606537631.25
    78 rdf:rest N543c448abb3842dcba7426226675eaa5
    79 Nba7d72ad353b4c01a48889c7de21e62a schema:name dimensions_id
    80 schema:value pub.1009948306
    81 rdf:type schema:PropertyValue
    82 Nc6103e1b4364447dbbf1e60463363e86 rdf:first Ne8b2a4b35fe4465d9ebdba7e83af115a
    83 rdf:rest N19fee603b41847dc94501094930a27ea
    84 Nc64007dd6266406e92bdcc279e7a1660 rdf:first sg:person.07453503162.70
    85 rdf:rest N4869b7d3adbf49ec93eac85ed8464061
    86 Nd92cbf8bfb5c42ebbee8ccf68c746836 schema:name Dpto. de Ingeniería Eléctrica y de Sistemas
    87 rdf:type schema:Organization
    88 Ndaa4a7ff7e8241949b9e4b5f9dd0aaf2 schema:familyName Ali
    89 schema:givenName Moonis
    90 rdf:type schema:Person
    91 Ne8b2a4b35fe4465d9ebdba7e83af115a schema:familyName Herrera
    92 schema:givenName Francisco
    93 rdf:type schema:Person
    94 Neb299f7d262f4d12b5e2e1eb33f74562 rdf:first Ndaa4a7ff7e8241949b9e4b5f9dd0aaf2
    95 rdf:rest rdf:nil
    96 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    97 schema:name Mathematical Sciences
    98 rdf:type schema:DefinedTerm
    99 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    100 schema:name Statistics
    101 rdf:type schema:DefinedTerm
    102 sg:person.010415303037.45 schema:affiliation N4026f94e02314299ac79cc38f9366304
    103 schema:familyName Fernández-Robles
    104 schema:givenName Laura
    105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010415303037.45
    106 rdf:type schema:Person
    107 sg:person.010551001361.75 schema:affiliation N7c6cd8084175445baca47f1fe5092739
    108 schema:familyName González-Castro
    109 schema:givenName Víctor
    110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010551001361.75
    111 rdf:type schema:Person
    112 sg:person.012606537631.25 schema:affiliation https://www.grid.ac/institutes/grid.4807.b
    113 schema:familyName Guzmán-Martínez
    114 schema:givenName R.
    115 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012606537631.25
    116 rdf:type schema:Person
    117 sg:person.016266057305.75 schema:affiliation Nd92cbf8bfb5c42ebbee8ccf68c746836
    118 schema:familyName Alegre
    119 schema:givenName Enrique
    120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016266057305.75
    121 rdf:type schema:Person
    122 sg:person.07453503162.70 schema:affiliation N3e326cf9a5cf4c37b1d282f4475b7c09
    123 schema:familyName Alaiz-Rodríguez
    124 schema:givenName Rocío
    125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07453503162.70
    126 rdf:type schema:Person
    127 sg:pub.10.1007/s10115-008-0139-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002914135
    128 https://doi.org/10.1007/s10115-008-0139-1
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/s10618-008-0097-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1013037105
    131 https://doi.org/10.1007/s10618-008-0097-y
    132 rdf:type schema:CreativeWork
    133 https://doi.org/10.1016/j.patcog.2008.01.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042374125
    134 rdf:type schema:CreativeWork
    135 https://doi.org/10.1016/s0167-8655(02)00390-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041018891
    136 rdf:type schema:CreativeWork
    137 https://doi.org/10.1145/1557019.1557117 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040178318
    138 rdf:type schema:CreativeWork
    139 https://doi.org/10.1162/089976602753284446 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005903963
    140 rdf:type schema:CreativeWork
    141 https://doi.org/10.1561/0100000004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068000263
    142 rdf:type schema:CreativeWork
    143 https://doi.org/10.3115/1220175.1220187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099221938
    144 rdf:type schema:CreativeWork
    145 https://www.grid.ac/institutes/grid.4807.b schema:alternateName University of Leon
    146 schema:name Servicio de Informatica y Comunicaciones, University of León, Campus de Vegazana s/n, 24071, León, Spain
    147 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...