Pages that link to "Item:Q2904219"
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The following pages link to Decision forests: a unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning (Q2904219):
Displaying 20 items.
- Comparison of machine learning methods for copper ore grade estimation (Q1715372) (← links)
- Machine learning based classification of normal, slow and fast walking by extracting multimodal features from stride interval time series (Q1980091) (← links)
- Dependence structure estimation using copula recursive trees (Q2048120) (← links)
- Towards convergence rate analysis of random forests for classification (Q2093392) (← links)
- Nonparametric feature selection by random forests and deep neural networks (Q2129580) (← links)
- Banzhaf random forests: cooperative game theory based random forests with consistency (Q2182870) (← links)
- End-to-end learning of decision trees and forests (Q2193582) (← links)
- Applicability and comparison of surrogate techniques for modeling of selected heating problems (Q2203542) (← links)
- A random forest guided tour (Q2629364) (← links)
- Entropic herding (Q2683495) (← links)
- (Q3440906) (← links)
- Forest Learning From Data and its Universal Coding (Q4562324) (← links)
- Tuning parameters in random forests (Q4606433) (← links)
- Predictive Distribution Modeling Using Transformation Forests (Q5066499) (← links)
- Piecewise Polynomial Approximation of Probability Density Functions with Application to Uncertainty Quantification for Stochastic PDEs (Q5141289) (← links)
- Cost-Complexity Pruning of Random Forests (Q5270552) (← links)
- Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks (Q5885833) (← links)
- A mathematical assessment of the isolation random forest method for anomaly detection in big data (Q6182044) (← links)
- Statistical computational learning (Q6602226) (← links)
- Discretized gradient flow for manifold learning (Q6610080) (← links)
