From 026c6f38d99f3e12db1cf40db0637408e1a5d318 Mon Sep 17 00:00:00 2001 From: Katrin Leinweber Date: Sat, 31 Mar 2018 12:53:25 +0200 Subject: [PATCH] Link DOIs to preferred resolver --- .../generated/sklearn.manifold.spectral_embedding.html | 4 ++-- .../generated/sklearn.metrics.matthews_corrcoef.html | 4 ++-- .../generated/sklearn.manifold.spectral_embedding.html | 4 ++-- .../generated/sklearn.metrics.matthews_corrcoef.html | 4 ++-- 0.17/_sources/modules/clustering.txt | 4 ++-- 0.17/modules/clustering.html | 6 +++--- .../generated/sklearn.manifold.spectral_embedding.html | 4 ++-- .../generated/sklearn.metrics.matthews_corrcoef.html | 4 ++-- 0.18/_sources/modules/clustering.txt | 4 ++-- 0.18/modules/clustering.html | 6 +++--- .../generated/sklearn.manifold.spectral_embedding.html | 4 ++-- .../generated/sklearn.metrics.matthews_corrcoef.html | 4 ++-- 0.19/_sources/modules/clustering.rst.txt | 4 ++-- 0.19/modules/clustering.html | 6 +++--- .../generated/sklearn.manifold.spectral_embedding.html | 4 ++-- .../generated/sklearn.metrics.matthews_corrcoef.html | 4 ++-- dev/_sources/modules/clustering.rst.txt | 4 ++-- dev/modules/clustering.html | 6 +++--- .../generated/sklearn.manifold.spectral_embedding.html | 4 ++-- .../generated/sklearn.metrics.matthews_corrcoef.html | 4 ++-- dev/modules/model_evaluation.html | 2 +- 21 files changed, 45 insertions(+), 45 deletions(-) diff --git a/0.15/modules/generated/sklearn.manifold.spectral_embedding.html b/0.15/modules/generated/sklearn.manifold.spectral_embedding.html index b12f2d8768f74..279dae21f1fb4 100644 --- a/0.15/modules/generated/sklearn.manifold.spectral_embedding.html +++ b/0.15/modules/generated/sklearn.manifold.spectral_embedding.html @@ -251,7 +251,7 @@

Toward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method Andrew V. Knyazev -http://dx.doi.org/10.1137%2FS1064827500366124 +https://doi.org/10.1137%2FS1064827500366124 @@ -307,4 +307,4 @@

- \ No newline at end of file + diff --git a/0.15/modules/generated/sklearn.metrics.matthews_corrcoef.html b/0.15/modules/generated/sklearn.metrics.matthews_corrcoef.html index 354a6a46fe4bd..56b89c2c6e3f8 100644 --- a/0.15/modules/generated/sklearn.metrics.matthews_corrcoef.html +++ b/0.15/modules/generated/sklearn.metrics.matthews_corrcoef.html @@ -222,7 +222,7 @@

-[R163]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the +[R163]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the accuracy of prediction algorithms for classification: an overview @@ -294,4 +294,4 @@

- \ No newline at end of file + diff --git a/0.16/modules/generated/sklearn.manifold.spectral_embedding.html b/0.16/modules/generated/sklearn.manifold.spectral_embedding.html index 754f1f5777086..025747339955c 100644 --- a/0.16/modules/generated/sklearn.manifold.spectral_embedding.html +++ b/0.16/modules/generated/sklearn.manifold.spectral_embedding.html @@ -257,7 +257,7 @@

Toward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method Andrew V. Knyazev -http://dx.doi.org/10.1137%2FS1064827500366124 +https://doi.org/10.1137%2FS1064827500366124 @@ -313,4 +313,4 @@

- \ No newline at end of file + diff --git a/0.16/modules/generated/sklearn.metrics.matthews_corrcoef.html b/0.16/modules/generated/sklearn.metrics.matthews_corrcoef.html index d71dd69895434..f5d4d7e3a2825 100644 --- a/0.16/modules/generated/sklearn.metrics.matthews_corrcoef.html +++ b/0.16/modules/generated/sklearn.metrics.matthews_corrcoef.html @@ -224,7 +224,7 @@

-[R171]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the +[R171]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the accuracy of prediction algorithms for classification: an overview @@ -296,4 +296,4 @@

- \ No newline at end of file + diff --git a/0.17/_sources/modules/clustering.txt b/0.17/_sources/modules/clustering.txt index 359feec7b4c44..7217f750d58ce 100644 --- a/0.17/_sources/modules/clustering.txt +++ b/0.17/_sources/modules/clustering.txt @@ -1158,7 +1158,7 @@ calculated using a similar form to that of the adjusted Rand index: * Vinh, Epps, and Bailey, (2009). "Information theoretic measures for clusterings comparison". Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09. - `doi:10.1145/1553374.1553511 `_. + `doi:10.1145/1553374.1553511 `_. ISBN 9781605585161. * Vinh, Epps, and Bailey, (2010). Information Theoretic Measures for @@ -1377,7 +1377,7 @@ cluster analysis. * Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis". Computational and Applied Mathematics 20: 53–65. - `doi:10.1016/0377-0427(87)90125-7 `_. + `doi:10.1016/0377-0427(87)90125-7 `_. Advantages diff --git a/0.17/modules/clustering.html b/0.17/modules/clustering.html index 4da311f7c4b14..4668dc4ce2459 100644 --- a/0.17/modules/clustering.html +++ b/0.17/modules/clustering.html @@ -1197,7 +1197,7 @@

2.3.9.2.3. Mathematical formulationVinh, Epps, and Bailey, (2009). “Information theoretic measures for clusterings comparison”. Proceedings of the 26th Annual International Conference on Machine Learning - ICML ‘09. -doi:10.1145/1553374.1553511. +doi:10.1145/1553374.1553511. ISBN 9781605585161.
  • Vinh, Epps, and Bailey, (2010). Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and @@ -1403,7 +1403,7 @@

    2.3.9.3.3. Mathematical formulationPeter J. Rousseeuw (1987). “Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis”. Computational and Applied Mathematics 20: 53–65. -doi:10.1016/0377-0427(87)90125-7.

    • +doi:10.1016/0377-0427(87)90125-7.
    @@ -1480,4 +1480,4 @@

    2.3.9.4.2. DrawbacksToward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method Andrew V. Knyazev -http://dx.doi.org/10.1137%2FS1064827500366124 +https://doi.org/10.1137%2FS1064827500366124 @@ -295,4 +295,4 @@

    - \ No newline at end of file + diff --git a/0.17/modules/generated/sklearn.metrics.matthews_corrcoef.html b/0.17/modules/generated/sklearn.metrics.matthews_corrcoef.html index bd642d6ed8e6b..88144193ee7fa 100644 --- a/0.17/modules/generated/sklearn.metrics.matthews_corrcoef.html +++ b/0.17/modules/generated/sklearn.metrics.matthews_corrcoef.html @@ -210,7 +210,7 @@

    -[R173]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the +[R173]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the accuracy of prediction algorithms for classification: an overview @@ -278,4 +278,4 @@

    - \ No newline at end of file + diff --git a/0.18/_sources/modules/clustering.txt b/0.18/_sources/modules/clustering.txt index 9f67b38856655..8068517e4134d 100644 --- a/0.18/_sources/modules/clustering.txt +++ b/0.18/_sources/modules/clustering.txt @@ -1474,7 +1474,7 @@ cluster analysis. * Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis". Computational and Applied Mathematics 20: 53–65. - `doi:10.1016/0377-0427(87)90125-7 `_. + `doi:10.1016/0377-0427(87)90125-7 `_. Advantages @@ -1567,4 +1567,4 @@ Drawbacks * Caliński, T., & Harabasz, J. (1974). "A dendrite method for cluster analysis". Communications in Statistics-theory and Methods 3: 1-27. - `doi:10.1080/03610926.2011.560741 `_. + `doi:10.1080/03610926.2011.560741 `_. diff --git a/0.18/modules/clustering.html b/0.18/modules/clustering.html index 2d7b4d139cf4d..f5951c4dbd2cd 100644 --- a/0.18/modules/clustering.html +++ b/0.18/modules/clustering.html @@ -1536,7 +1536,7 @@

    2.3.9.4.2. Drawbacksdoi:10.1016/0377-0427(87)90125-7. +doi:10.1016/0377-0427(87)90125-7.

    @@ -1681,4 +1681,4 @@

    2.3.9.6.2. DrawbacksToward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method Andrew V. Knyazev -http://dx.doi.org/10.1137%2FS1064827500366124 +https://doi.org/10.1137%2FS1064827500366124 @@ -329,4 +329,4 @@

    - \ No newline at end of file + diff --git a/0.18/modules/generated/sklearn.metrics.matthews_corrcoef.html b/0.18/modules/generated/sklearn.metrics.matthews_corrcoef.html index 90dd5287d977d..e7521295f9434 100644 --- a/0.18/modules/generated/sklearn.metrics.matthews_corrcoef.html +++ b/0.18/modules/generated/sklearn.metrics.matthews_corrcoef.html @@ -244,7 +244,7 @@

    -[R218]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the +[R218]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the accuracy of prediction algorithms for classification: an overview @@ -316,4 +316,4 @@

    - \ No newline at end of file + diff --git a/0.19/_sources/modules/clustering.rst.txt b/0.19/_sources/modules/clustering.rst.txt index 4a5d15b775e79..c569eabfd7b78 100644 --- a/0.19/_sources/modules/clustering.rst.txt +++ b/0.19/_sources/modules/clustering.rst.txt @@ -1488,7 +1488,7 @@ cluster analysis. * Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis". Computational and Applied Mathematics 20: 53–65. - `doi:10.1016/0377-0427(87)90125-7 `_. + `doi:10.1016/0377-0427(87)90125-7 `_. Advantages @@ -1581,4 +1581,4 @@ Drawbacks * Caliński, T., & Harabasz, J. (1974). "A dendrite method for cluster analysis". Communications in Statistics-theory and Methods 3: 1-27. - `doi:10.1080/03610926.2011.560741 `_. + `doi:10.1080/03610926.2011.560741 `_. diff --git a/0.19/modules/clustering.html b/0.19/modules/clustering.html index 656aa96dd072c..d5dfeb3007f4d 100644 --- a/0.19/modules/clustering.html +++ b/0.19/modules/clustering.html @@ -1549,7 +1549,7 @@

    2.3.9.4.2. Drawbacksdoi:10.1016/0377-0427(87)90125-7. +doi:10.1016/0377-0427(87)90125-7. @@ -1691,4 +1691,4 @@

    2.3.9.6.2. DrawbacksToward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method Andrew V. Knyazev -http://dx.doi.org/10.1137%2FS1064827500366124 +https://doi.org/10.1137%2FS1064827500366124 @@ -333,4 +333,4 @@

    - \ No newline at end of file + diff --git a/0.19/modules/generated/sklearn.metrics.matthews_corrcoef.html b/0.19/modules/generated/sklearn.metrics.matthews_corrcoef.html index ba121885be08d..16f1dbb93acc3 100644 --- a/0.19/modules/generated/sklearn.metrics.matthews_corrcoef.html +++ b/0.19/modules/generated/sklearn.metrics.matthews_corrcoef.html @@ -248,7 +248,7 @@

    -[R221]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the +[R221]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the accuracy of prediction algorithms for classification: an overview @@ -331,4 +331,4 @@

    - \ No newline at end of file + diff --git a/dev/_sources/modules/clustering.rst.txt b/dev/_sources/modules/clustering.rst.txt index e6c5342fb14eb..df2e890af9a71 100644 --- a/dev/_sources/modules/clustering.rst.txt +++ b/dev/_sources/modules/clustering.rst.txt @@ -1496,7 +1496,7 @@ cluster analysis. * Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis". Computational and Applied Mathematics 20: 53–65. - `doi:10.1016/0377-0427(87)90125-7 `_. + `doi:10.1016/0377-0427(87)90125-7 `_. Advantages @@ -1589,7 +1589,7 @@ Drawbacks * Caliński, T., & Harabasz, J. (1974). "A dendrite method for cluster analysis". Communications in Statistics-theory and Methods 3: 1-27. - `doi:10.1080/03610926.2011.560741 `_. + `doi:10.1080/03610926.2011.560741 `_. .. _contingency_matrix: diff --git a/dev/modules/clustering.html b/dev/modules/clustering.html index 2676cb4ebf9ca..6aa04773ac8cc 100644 --- a/dev/modules/clustering.html +++ b/dev/modules/clustering.html @@ -1573,7 +1573,7 @@

    2.3.9.4.2. Drawbacksdoi:10.1016/0377-0427(87)90125-7. +doi:10.1016/0377-0427(87)90125-7. @@ -1765,4 +1765,4 @@

    2.3.9.7.2. DrawbacksToward the Optimal Preconditioned Eigensolver: Locally Optimal Block Preconditioned Conjugate Gradient Method Andrew V. Knyazev -http://dx.doi.org/10.1137%2FS1064827500366124 +https://doi.org/10.1137%2FS1064827500366124 @@ -331,4 +331,4 @@

    - \ No newline at end of file + diff --git a/dev/modules/generated/sklearn.metrics.matthews_corrcoef.html b/dev/modules/generated/sklearn.metrics.matthews_corrcoef.html index 09488234ed4bb..0dfc878e2a4c9 100644 --- a/dev/modules/generated/sklearn.metrics.matthews_corrcoef.html +++ b/dev/modules/generated/sklearn.metrics.matthews_corrcoef.html @@ -250,7 +250,7 @@

    -[1]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the +[1]Baldi, Brunak, Chauvin, Andersen and Nielsen, (2000). Assessing the accuracy of prediction algorithms for classification: an overview @@ -333,4 +333,4 @@

    - \ No newline at end of file + diff --git a/dev/modules/model_evaluation.html b/dev/modules/model_evaluation.html index 96bcd86e683b9..6793366b1fdcb 100644 --- a/dev/modules/model_evaluation.html +++ b/dev/modules/model_evaluation.html @@ -2090,4 +2090,4 @@

    3.3.2.9.2. Multiclass and multilabel classification - \ No newline at end of file +