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1. Full Text A random forest guided tour
by Biau, Gérard and Scornet, Erwan
Test (Madrid, Spain), ISSN 1133-0686, 6/2016, Volume 25, Issue 2, pp. 197 - 227
Randomization | Statistics for Business/Economics/Mathematical Finance/Insurance | Variable importance | Parameter tuning | Statistical Theory and Methods | Statistics, general | Resampling | Statistics | 62G02 | Random forests | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Algorithms | Studies | Regression analysis | Decision trees | Learning | Tasks | Aggregates | Mathematical analysis | Classification | Regression
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2. Full Text Forest PA: Constructing a decision forest by penalizing attributes used in previous trees
by Adnan, Md Nasim and Islam, Md Zahidul
Expert systems with applications, ISSN 0957-4174, 12/2017, Volume 89, pp. 389 - 403
Ensemble Accuracy | Decision Tree | Classification | Decision Forest | Random Forest | Operations Research & Management Science | Engineering | Technology | Computer Science | Engineering, Electrical & Electronic | Computer Science, Artificial Intelligence | Science & Technology | Algorithms | Machine learning | Decision trees | Experiments | Expert systems | Intelligent systems | System effectiveness
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3. Full Text CONSISTENCY OF RANDOM FORESTS
by Erwan Scornet and Gérard Biau and Jean-Philippe Vert
The Annals of statistics, ISSN 0090-5364, 8/2015, Volume 43, Issue 4, pp. 1716 - 1741
Dimension reduction | Randomization | Sparsity | Additive model | Random forests | Consistency | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Algorithms | Mathematical analysis | Mathematical models | Regression analysis | Decision trees | Statistics | Machine Learning | Statistics Theory | 62G05 | additive model | randomization | 62G20 | sparsity | consistency | dimension reduction
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4. Full Text Heterogeneous oblique random forest
by Katuwal, Rakesh and Suganthan, P.N and Zhang, Le
Pattern recognition, ISSN 0031-3203, 03/2020, Volume 99, p. 107078
Classifiers | Benchmarking | Heterogeneous | Oblique random forest | Ensemble learning | One-vs-all | Engineering, Electrical & Electronic | Engineering | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology
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5. Full Text Random Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features
by Du, Peijun and Samat, Alim and Waske, Björn and Liu, Sicong and Li, Zhenhong
ISPRS journal of photogrammetry and remote sensing, ISSN 0924-2716, 07/2015, Volume 105, pp. 38 - 53
Polarimetric SAR | Rotation Forest | Morphological profiles | Ensemble learning | Textural feature | Image classification | Random Forest | Geosciences, Multidisciplinary | Physical Sciences | Geology | Technology | Physical Geography | Geography, Physical | Remote Sensing | Imaging Science & Photographic Technology | Science & Technology | Artificial satellites in remote sensing | Analysis | Learning strategies | Synthetic aperture radar
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6. Full Text Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling
by Chen, Wei and Zhang, Shuai and Li, Renwei and Shahabi, Himan
The Science of the total environment, ISSN 0048-9697, 12/2018, Volume 644, pp. 1006 - 1018
Landslide | Random forest | naïve Bayes tree | China | Best-first decision tree | Environmental Sciences & Ecology | Life Sciences & Biomedicine | Science & Technology | Environmental Sciences | Landslides | Geomorphology | Analysis | Models | Data mining | Methods | Geographic information systems
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7. Full Text A Siamese Deep Forest
by Utkin, Lev V and Ryabinin, Mikhail A
Knowledge-based systems, ISSN 0950-7051, 01/2018, Volume 139, pp. 13 - 22
Deep learning | Quadratic optimization | Classification | Siamese | Random forest | Decision tree | Metric learning | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Neural networks | Training | Forests | Artificial intelligence | Optimization
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8. Full Text Reinforced quasi-random forest
by Paul, Angshuman and Mukherjee, Dipti Prasad
Pattern recognition, ISSN 0031-3203, 10/2019, Volume 94, pp. 13 - 24
Orthogonal decision trees | Importance of attributes | Random forest | Reinforcement learning | Engineering, Electrical & Electronic | Engineering | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology
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9. Full Text Random Forest based hourly building energy prediction
by Wang, Zeyu and Wang, Yueren and Zeng, Ruochen and Srinivasan, Ravi S and Ahrentzen, Sherry
Energy and buildings, ISSN 0378-7788, 07/2018, Volume 171, pp. 11 - 25
Ensemble model Machine learning | Regression tree | Random forest | Building energy use prediction | Engineering | Technology | Construction & Building Technology | Engineering, Civil | Energy & Fuels | Science & Technology | Energy consumption | Architecture and energy conservation | Energy efficiency | Business schools | School construction | Machine learning | Performance indices | Parameters | Buildings | Performance prediction | Regression analysis | Empirical analysis | Energy usage | Support vector machines | Education | Mathematical models | Artificial intelligence
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10.