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<h1 class="title">Bilan semaine 18 2025 : 28 avril - 2 mai</h1>
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<div class="quarto-categories">
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<div class="quarto-category">colBiSBM</div>
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<div class="quarto-category">inférence</div>
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<div class="quarto-title-meta-heading">Auteur·rice</div>
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<div class="quarto-title-meta-heading">Affiliation</div>
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<div class="quarto-title-meta-contents">
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<p class="author">Louis Lacoste <a href="mailto:louis.lacoste@agroparistech.fr" class="quarto-title-author-email"><i class="bi bi-envelope"></i></a> <a href="https://orcid.org/0009-0004-0178-9821" class="quarto-title-author-orcid"> <img src="data:image/png;base64,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"></a></p>
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</div>
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<div class="quarto-title-meta-contents">
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<p class="affiliation">
|
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MIA Paris-Saclay, INRAE, AgroParisTech, Université Paris-Saclay
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</p>
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<div class="quarto-title-meta-heading">Date de publication</div>
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<p class="date">2 mai 2025</p>
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<div class="quarto-title-meta-heading">Modifié</div>
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<p class="date-modified">26 août 2025</p>
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<h2 id="toc-title">Sur cette page</h2>
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<li><a href="#stratégie-suite-inférence" id="toc-stratégie-suite-inférence" class="nav-link" data-scroll-target="#stratégie-suite-inférence">Stratégie suite : Inférence</a></li>
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</ul></li>
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<li><a href="#jai-fait" id="toc-jai-fait" class="nav-link" data-scroll-target="#jai-fait">J’ai fait</a>
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<li><a href="#jds" id="toc-jds" class="nav-link" data-scroll-target="#jds">JdS</a></li>
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<li><a href="#clustering-exhaustif-baldock" id="toc-clustering-exhaustif-baldock" class="nav-link" data-scroll-target="#clustering-exhaustif-baldock">Clustering exhaustif Baldock</a></li>
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<li><a href="#applications-1" id="toc-applications-1" class="nav-link" data-scroll-target="#applications-1">Applications</a></li>
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<section id="a-faire" class="level2">
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<h2 class="anchored" data-anchor-id="a-faire">A faire</h2>
|
||
<section id="stratégie-suite-inférence" class="level3">
|
||
<h3 class="anchored" data-anchor-id="stratégie-suite-inférence">Stratégie suite : Inférence</h3>
|
||
<ul>
|
||
<li><p>Lire biblio fournie Julie, Inférence de réseaux : co-occurence</p></li>
|
||
<li><p>Papier pour comprendre données</p></li>
|
||
<li><p>pbs : variance, bcp de zero, covariables, offset et taxonomie (Reseaux arretes differents niveaux : Genre, OTU …)</p></li>
|
||
</ul>
|
||
<blockquote class="blockquote">
|
||
<p>Combine networks at different taxonomic levels</p>
|
||
</blockquote>
|
||
<ul>
|
||
<li>Inférence + GREMLINS</li>
|
||
</ul>
|
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</section>
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<section id="rédaction-article" class="level3">
|
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<h3 class="anchored" data-anchor-id="rédaction-article">Rédaction article</h3>
|
||
<ul>
|
||
<li><p>Relire intro St Clair</p></li>
|
||
<li><p>S’inspirer structure pour mon intro</p></li>
|
||
<li><p>Trouver biblio intro</p></li>
|
||
<li><p>Rédiger l’intro</p></li>
|
||
<li><p>Regarder les applications pour les collections de réseaux recommender system</p></li>
|
||
<li><p>Lire les papiers de Baldock Traveset Souza Cordeniz Trojelsgaard et Gibson</p></li>
|
||
<li><p>Dire résultats nettement meilleurs et variabilités inférieures.</p></li>
|
||
<li><p>Intégrer les retours de Sophie</p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="simulations-article" class="level3">
|
||
<h3 class="anchored" data-anchor-id="simulations-article">Simulations article</h3>
|
||
<ul>
|
||
<li><p>Comparer sur clustering unipartite avec versions symétriser des par blocs des matrices d’adjacences.</p></li>
|
||
<li><p>Corriger structure de simus :</p>
|
||
<ul>
|
||
<li>Pour noisy <span class="math inline">\alpha</span> :
|
||
<ul>
|
||
<li>Logit pour envoyer la gaussienne vers (0,1)</li>
|
||
<li>Beta contrainte dans (0,1)</li>
|
||
</ul></li>
|
||
<li>Pour noisy links : Générer <code>nb_clustering</code> collections de taille M puis prélever <span class="math inline">\epsilon_{max}n_r n_c</span> liens à inverser puis pour les <span class="math inline">\epsilon < \epsilon_{max}</span> prélever dans la liste des indices afin d’avoir des perturbations emboitées.</li>
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||
</ul></li>
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||
</ul>
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||
</section>
|
||
<section id="applications" class="level3">
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<h3 class="anchored" data-anchor-id="applications">Applications</h3>
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||
<ul>
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||
<li>Kmeans sur la densité des réseaux subdoré pour pré-partitionner et <em>clusteriser</em>. Car densités déséquilibrées.</li>
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||
</ul>
|
||
<p><a href="figs/density-subdore.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1"><img src="figs/density-subdore.png" class="img-fluid"></a></p>
|
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</section>
|
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<section id="autour-de-larticle-et-du-package" class="level3">
|
||
<h3 class="anchored" data-anchor-id="autour-de-larticle-et-du-package">Autour de l’article et du package</h3>
|
||
<ul>
|
||
<li>Créer des vignettes illustrant par exemple des cas de simulations. <strong>Possible de mettre l’exemple d’application de Sophie sur les réseaux avec gradient d’urbanisation</strong>.</li>
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||
</ul>
|
||
</section>
|
||
</section>
|
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<section id="jai-fait" class="level2">
|
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<h2 class="anchored" data-anchor-id="jai-fait">J’ai fait</h2>
|
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<section id="jds" class="level3">
|
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<h3 class="anchored" data-anchor-id="jds">JdS</h3>
|
||
<ul>
|
||
<li>colDEM CSE</li>
|
||
</ul>
|
||
</section>
|
||
<section id="clustering-exhaustif-baldock" class="level3">
|
||
<h3 class="anchored" data-anchor-id="clustering-exhaustif-baldock">Clustering exhaustif Baldock</h3>
|
||
<ul>
|
||
<li><p>Le clustering de toutes les 52 partitions s’est fait en 5h30 ! (Mémoïsation)</p></li>
|
||
<li><p>Pour iid la meilleure partition avec <span class="math inline">BICL=-9466.911</span> contre <span class="math inline">BICL_{algo} = -9466.873 \pm 0.02205</span> trouvé avec l’algo <img src="figs/partition-iid.svg" class="img-fluid" alt="best_iid"></p></li>
|
||
<li><p>Pour <span class="math inline">\pi\rho</span> la meilleure partition avec <span class="math inline">BICL = -9497.92</span> contre <span class="math inline">BICL_{algo} =-9497.92 \pm 0.00009</span> <img src="figs/partition-pirho.svg" class="img-fluid" alt="best_pirho"></p></li>
|
||
</ul>
|
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</section>
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</section>
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<h2 class="anchored" data-anchor-id="a-continuer">A continuer</h2>
|
||
<ul>
|
||
<li><p>Résultats simus NA <strong>Erreur pour certaines conditions</strong> : Pour NA robustness générer <code>nb_rep</code> collections de taille <span class="math inline">M=2</span> et prélever <span class="math inline">\epsilon_{max}n_r n_c</span> liens à retirer puis pour les <span class="math inline">\epsilon < \epsilon_{max}</span> prélever dans la liste des indices afin d’avoir des perturbations emboitées. Il faut que j’ajoute un mécanisme pour reprendre des conditions qui ont plantés et que je skip dans le future_lapply les conditions déjà traitées (pour avoir la même seed quand je vais exécuter le code). Implémenté les missing steps <em>en attente des résultats MIGALE</em>.</p></li>
|
||
<li><p>Lire Biological Networks - François Képès</p></li>
|
||
<li><p>Relancer simus d’inférence avec n = 240 pour voir si la qualité augmenter (se rassurer). En fait on est déjà à 240, j’ai relancé avec M = 4 au lieu de M = 2. En attente résultats MIGALE</p></li>
|
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</ul>
|
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<section id="applications-1" class="level3">
|
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<h3 class="anchored" data-anchor-id="applications-1">Applications</h3>
|
||
<ul>
|
||
<li>Idée Sophie: Regarder clustering de données plantes-pollinisateur selon gradient d’urbanisation</li>
|
||
</ul>
|
||
<blockquote class="blockquote">
|
||
<p>Sophie a fait une appli qui marche bien et va dans le sens de l’analyse faite (à savoir pas d’effet du gradien d’urbanisation). À continuer pour l’intégrer dans l’article !</p>
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<h3 class="anchored" data-anchor-id="simulations-article-1">Simulations article</h3>
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})();
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</script>
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</body></html> |