• Suche: Interpretable Machine Learning with Python

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241

Dynamic Logistic Ensembles with Recursive Probability and Automatic Subset Splitting for Enhanced Binary Classification
Khan, Mohammad Zubair ; Li, David

Computer Science - Machi... Computer Science - Artif...
Report
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242

Feature engineering through two-level genetic algorithm
Aditi Gulati ; Armin Felahatpisheh ; Camilo E. Valderrama
Machine Learning with Applications, Vol 21, Iss , Pp 100696- (2025)

Feature engineering Multi-objective genetic... Ensemble learning Machine learning Feature selection Model interpretability …
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243

Machine learning-assisted sensing platform for simultaneous and visual detection of tetracycline hydrochloride and ofloxacin.
Zhang, Meng ; Kong, Yiming ; Wang, Haochen ; et al.
Biosensors & Bioelectronics. Feb2026, Vol. 293, pN.PAG-N.PAG. 1p.

TETRACYCLINE ANTIBIOTICS BIOSENSORS MACHINE learning FLUORESCENT dyes POLLUTION
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244

Automated Lesion and Feature Extraction Pipeline for Brain MRIs with Interpretability.
Eghbali, Reza ; Nedelec, Pierre ; Weiss, David ; et al.
Neuroinformatics. 23(1)

MRI pipeline Neuroradiology Radiomics Humans Magnetic Resonance Imagi... Brain …
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245

Intelligent Data: Revolutionizing Analytics with AI and Python
Murali Krishna Pasupuleti ; Murali Krishna Pasupuleti

Buch
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246

Interpretable serious event forecasting using machine learning and SHAP
Gustafsson, Sebastian

LSTM GBDT SHAP ML AI Computer Sciences …
Dissertation
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247

Applying BERT and ChatGPT for Sentiment Analysis of Lyme Disease in Scientific Literature.
Susnjak T
Publisher: Humana Press Country of Publication: United States NLM ID: 9214969 Publication Model: Print Cited Medium: Internet ISSN: 1940-6029 (Electronic) Linking ISSN: 10643745 NLM ISO Abbreviation: Methods Mol Biol Subsets: MEDLINE

Humans Publications Language Machine Learning Sentiment Analysis Lyme Disease
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248

csinva/imodels python package for interpretable modeling
Chandan Singh

Interpretability Machine-learning Rules
E-Ressource
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249

Validation-Free Sparse Learning: A Phase Transition Approach to Feature Selection
Sardy, Sylvain ; van Cutsem, Maxime ; Ma, Xiaoyu

Machine Learning
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250

E01Loss: A Python library for solving the exact 0-1 loss linear classification problem
Xi He ; Max A. Little ; orcid:0000-0002-4284-

Interpretable machine le... Combinatorial optimizati... Hyperplane arrangement Exact algorithm
E-Ressource
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251

The Potential of a CT-Based Machine Learning Radiomics Analysis to Differentiate Brucella and Pyogenic Spondylitis.
Yasin, Parhat ; Mardan, Muradil ; Abliz, Dilxat ; et al.
Journal of Inflammation Research; Nov2023, Vol. 16, p5585-5600, 16p

URUMQI (China) CHINA SPONDYLITIS RADIOMICS MACHINE learning RECEIVER operating chara... …
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252

Fractional ridge regression: a fast, interpretable reparameterization of ridge regression
Ariel Rokem ; Kendrick Kay
Gigascience

FOS: Computer and inform... Computer Science - Machi... Brain Machine Learning (stat.M... 01 natural sciences Machine Learning (cs.LG) …
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253

Performance Evaluation of Decision Trees with Machine Learning Algorithm
Kiran Nitin Babar
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. :1-5

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254

Stacked regressions and structured variance partitioning for interpretable brain maps
Lin, Ruogu ; Naselaris, Thomas ; Kay, Kendrick ; et al.
In NeuroImage September 2024 298

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255

Learning Transformer Programs
Friedman, Dan ; Wettig, Alexander ; Chen, Danqi

Computer Science - Machi... Computer Science - Compu...
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256

Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Hollmann, Noah ; Müller, Samuel ; Hutter, Frank

Computer Science - Artif... Computer Science - Machi...
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257

Mixture of Decision Trees for Interpretable Machine Learning
Brüggenjurgen, Simeon ; Schaaf, Nina ; Kerschke, Pascal ; et al.

decision trees ensemble explainability interpretability machine learnin mixture of experts
Konferenz
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258

The Potential of a CT-Based Machine Learning Radiomics Analysis to Differentiate Brucella and Pyogenic Spondylitis
Parhat Yasin ; Muradil Mardan ; Dilxat Abliz ; et al.
J Inflamm Res
Journal of Inflammation Research, Vol Volume 16, Pp 5585-5600 (2023)

pyogenic spondylitis machine learning model interpretation radiomics Pathology RB1-214 …
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259

AAclust: k-optimized clustering for selecting redundancy-reduced sets of amino acid scales.
Breimann, Stephan ; Frishman, Dmitrij
Bioinformatics Advances. 2024, Vol. 4 Issue 1, p1-6. 6p.

MACHINE learning AMINO acids PROTEIN models MODELS & modelmaking WRAPPERS
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260

PiNN : A Python Library for Building Atomic Neural Networks of Molecules and Materials
Shao, Yunqi ; Hellström, Matti ; Mitev, Pavlin D. ; et al.

E-Ressource
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