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#modelselection

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Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #393 Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements [actual post]</p><p>Thoughts: #392 has the comments, but this is where the magic happens.</p><p><a href="https://mastodon.social/tags/modelselection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelselection</span></a> <a href="https://mastodon.social/tags/modelcomparison" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelcomparison</span></a> <a href="https://mastodon.social/tags/variance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>variance</span></a> <a href="https://mastodon.social/tags/effectsize" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>effectsize</span></a> <a href="https://mastodon.social/tags/tutorial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tutorial</span></a></p><p><a href="https://www.fharrell.com/post/addvalue/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">fharrell.com/post/addvalue/</span><span class="invisible"></span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #392 Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements (forum thread)</p><p>Thoughts: Forums can be great for asking the author for exact answers to complex questions</p><p><a href="https://mastodon.social/tags/modelselection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelselection</span></a> <a href="https://mastodon.social/tags/causalinference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>causalinference</span></a> <a href="https://mastodon.social/tags/prediction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>prediction</span></a> <a href="https://mastodon.social/tags/bias" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bias</span></a> <a href="https://mastodon.social/tags/information" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>information</span></a></p><p><a href="https://discourse.datamethods.org/t/statistically-efficient-ways-to-quantify-added-predictive-value-of-new-measurements/2013/1" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">discourse.datamethods.org/t/st</span><span class="invisible">atistically-efficient-ways-to-quantify-added-predictive-value-of-new-measurements/2013/1</span></a></p>
Europe Says<p><a href="https://www.europesays.com/2228357/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">europesays.com/2228357/</span><span class="invisible"></span></a> Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks <a href="https://pubeurope.com/tags/Clustering" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Clustering</span></a> <a href="https://pubeurope.com/tags/ComputationalBiologyAndBioinformatics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalBiologyAndBioinformatics</span></a> <a href="https://pubeurope.com/tags/ComputationalComplexity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ComputationalComplexity</span></a> <a href="https://pubeurope.com/tags/Data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Data</span></a> <a href="https://pubeurope.com/tags/engineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>engineering</span></a> <a href="https://pubeurope.com/tags/HumanitiesAndSocialSciences" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HumanitiesAndSocialSciences</span></a> <a href="https://pubeurope.com/tags/LogisticRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LogisticRegression</span></a> <a href="https://pubeurope.com/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://pubeurope.com/tags/ModelSelection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ModelSelection</span></a> <a href="https://pubeurope.com/tags/Modularity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Modularity</span></a> <a href="https://pubeurope.com/tags/multidisciplinary" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>multidisciplinary</span></a> <a href="https://pubeurope.com/tags/NetworkInference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NetworkInference</span></a> <a href="https://pubeurope.com/tags/NetworkScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NetworkScience</span></a> <a href="https://pubeurope.com/tags/RandomForest" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RandomForest</span></a> <a href="https://pubeurope.com/tags/ScaleFreeNetworks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScaleFreeNetworks</span></a> <a href="https://pubeurope.com/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a></p>
Dr Mircea Zloteanu ☀️ 🌊🌴<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statstab</span></a> #358 What are some of the problems with stepwise regression?</p><p>Thoughts: Model selection is not an easy task, but maybe don't naively try step wise reg.</p><p><a href="https://mastodon.social/tags/stepwise" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stepwise</span></a> <a href="https://mastodon.social/tags/regression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>regression</span></a> <a href="https://mastodon.social/tags/QRPs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>QRPs</span></a> <a href="https://mastodon.social/tags/issues" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>issues</span></a> <a href="https://mastodon.social/tags/phacking" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>phacking</span></a> <a href="https://mastodon.social/tags/modelselection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelselection</span></a> <a href="https://mastodon.social/tags/bias" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bias</span></a></p><p><a href="https://www.stata.com/support/faqs/statistics/stepwise-regression-problems/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">stata.com/support/faqs/statist</span><span class="invisible">ics/stepwise-regression-problems/</span></a></p>
SRF IRIS<p>IRIS Insights I Nico Formanek: Are hyperparameters vibes?<br>April 24, 2025, 2:00 p.m. (CEST)<br>Our second IRIS Insights talk will take place with Nico Formanek.<br>🟦 <br>This talk will discuss the role of hyperparameters in optimization methods for model selection (currently often called ML) from a philosophy of science point of view. Special consideration is given to the question of whether there can be principled ways to fix hyperparameters in a maximally agnostic setting.<br>🟦 <br>This is a WebEx talk to which everyone who is interested is cordially invited. It will take place in English. Our IRIS speaker, Jun.-Prof. Dr. Maria Wirzberger, will moderate it. Following Nico Formanek's presentation, there will be an opportunity to ask questions. We look forward to active participation.<br>🟦 <br>Please join this Webex talk using the following link:<br><a href="https://lnkd.in/eJNiUQKV" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">lnkd.in/eJNiUQKV</span><span class="invisible"></span></a><br>🟦 <br><a href="https://xn--baw-joa.social/tags/Hyperparameters" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Hyperparameters</span></a> <a href="https://xn--baw-joa.social/tags/ModelSelection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ModelSelection</span></a> <a href="https://xn--baw-joa.social/tags/Optimization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Optimization</span></a> <a href="https://xn--baw-joa.social/tags/MLMethods" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MLMethods</span></a> <a href="https://xn--baw-joa.social/tags/PhilosophyOfScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PhilosophyOfScience</span></a> <a href="https://xn--baw-joa.social/tags/ScientificMethod" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScientificMethod</span></a> <a href="https://xn--baw-joa.social/tags/AgnosticLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AgnosticLearning</span></a> <a href="https://xn--baw-joa.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://xn--baw-joa.social/tags/InterdisciplinaryResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>InterdisciplinaryResearch</span></a> <a href="https://xn--baw-joa.social/tags/AIandPhilosophy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIandPhilosophy</span></a> <a href="https://xn--baw-joa.social/tags/EthicsInAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EthicsInAI</span></a> <a href="https://xn--baw-joa.social/tags/ResponsibleAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ResponsibleAI</span></a> <a href="https://xn--baw-joa.social/tags/AITheory" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AITheory</span></a> <a href="https://xn--baw-joa.social/tags/WebTalk" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WebTalk</span></a> <a href="https://xn--baw-joa.social/tags/OnlineLecture" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OnlineLecture</span></a> <a href="https://xn--baw-joa.social/tags/ResearchTalk" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ResearchTalk</span></a> <a href="https://xn--baw-joa.social/tags/ScienceEvents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ScienceEvents</span></a> <a href="https://xn--baw-joa.social/tags/OpenInvitation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenInvitation</span></a> <a href="https://xn--baw-joa.social/tags/AICommunity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AICommunity</span></a> <a href="https://xn--baw-joa.social/tags/LinkedInScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LinkedInScience</span></a> <a href="https://xn--baw-joa.social/tags/TechPhilosophy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechPhilosophy</span></a> <a href="https://xn--baw-joa.social/tags/AIConversations" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIConversations</span></a></p>