#modelselection - Sigmoid Social

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Hacker News @h4ckernews@mastodon.social

Not So Prompt: Prompt Optimization as Model Selection

https://www.gojiberries.io/not-so-prompt-prompt-optimization-as-model-selection/

Gojiberries · Aug 12, 2024Not so Prompt: Prompt Optimization as Model SelectionHere's a framework for prompt optimization: Defining Success: Metrics and Evaluation Criteria Before collecting any data, establish what success looks like for your specific use case. Choose a primary metric that directly reflects business value—accuracy for classification, F1 for imbalanced datasets, BLEU/ROUGE for generation tasks, or custom domain-specific

#HackerNews #PromptOptimization #ModelSelection

Dr Mircea Zloteanu @mzloteanu@mastodon.social

#statstab #393 Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements [actual post]

Thoughts: #392 has the comments, but this is where the magic happens.

#modelselection #modelcomparison #variance #effectsize #tutorial

https://www.fharrell.com/post/addvalue/

Statistical ThinkingStatistically Efficient Ways to Quantify Added Predictive Value of New Measurements – Statistical ThinkingResearchers have used contorted, inefficient, and arbitrary analyses to demonstrated added value in biomarkers, genes, and new lab measurements. Traditional statistical measures have always been up to the task, and are more powerful and more flexible. It’s time to revisit them, and to add a few slight twists to make them more helpful.

Dr Mircea Zloteanu @mzloteanu@mastodon.social

#statstab #392 Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements (forum thread)

Thoughts: Forums can be great for asking the author for exact answers to complex questions

#modelselection #causalinference #prediction #bias #information

https://discourse.datamethods.org/t/statistically-efficient-ways-to-quantify-added-predictive-value-of-new-measurements/2013/1

Datamethods Discussion Forum · Aug 22, 2019Statistically Efficient Ways to Quantify Added Predictive Value of New MeasurementsThis topic is for discussions about Statistically Efficient Ways to Quantify Added Predictive Value of New Measurements

Europe Says @europesays@pubeurope.com

https://www.europesays.com/2228357/ Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks #Clustering #ComputationalBiologyAndBioinformatics #ComputationalComplexity #Data #engineering #HumanitiesAndSocialSciences #LogisticRegression #MachineLearning #ModelSelection #Modularity #multidisciplinary #NetworkInference #NetworkScience #RandomForest #ScaleFreeNetworks #science

Dr Mircea Zloteanu @mzloteanu@mastodon.social

#statstab #358 What are some of the problems with stepwise regression?

Thoughts: Model selection is not an easy task, but maybe don't naively try step wise reg.

#stepwise #regression #QRPs #issues #phacking #modelselection #bias

https://www.stata.com/support/faqs/statistics/stepwise-regression-problems/

www.stata.comStata | FAQ: Problems with stepwise regressionWhat are some of the problems with stepwise regression?

SRF IRIS @Stuttgart_IRIS@bawü.social

IRIS Insights I Nico Formanek: Are hyperparameters vibes?
April 24, 2025, 2:00 p.m. (CEST)
Our second IRIS Insights talk will take place with Nico Formanek.

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.

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.

Please join this Webex talk using the following link:
https://lnkd.in/eJNiUQKV

#Hyperparameters #ModelSelection #Optimization #MLMethods #PhilosophyOfScience #ScientificMethod #AgnosticLearning #MachineLearning #InterdisciplinaryResearch #AIandPhilosophy #EthicsInAI #ResponsibleAI #AITheory #WebTalk #OnlineLecture #ResearchTalk #ScienceEvents #OpenInvitation #AICommunity #LinkedInScience #TechPhilosophy #AIConversations

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