The following pages link to UCI-ml (Q16261):
Displaying 50 items.
- Instance spaces for machine learning classification (Q1707470) (← links)
- Learning data discretization via convex optimization (Q1707483) (← links)
- Privacy preserving and fast decision for novelty detection using support vector data description (Q1708732) (← links)
- Learning a symbolic representation for multivariate time series classification (Q1711227) (← links)
- Linear regression with sparsely permuted data (Q1711600) (← links)
- Boosting imbalanced data learning with Wiener process oversampling (Q1712569) (← links)
- Multi-period classification: learning sequent classes from temporal domains (Q1715877) (← links)
- Mining outlying aspects on numeric data (Q1715883) (← links)
- Cluster validity functions for categorical data: a solution-space perspective (Q1715908) (← links)
- A general framework for never-ending learning from time series streams (Q1715913) (← links)
- Discrimination- and privacy-aware patterns (Q1715918) (← links)
- Properties of the sample estimators used for statistical normalization of feature vectors (Q1715923) (← links)
- Least absolute deviation support vector regression (Q1717816) (← links)
- A new nearest neighbor classification algorithm based on local probability centers (Q1718136) (← links)
- Cost-sensitive attribute reduction in decision-theoretic rough set models (Q1719302) (← links)
- Adaptive linear and normalized combination of radial basis function networks for function approximation and regression (Q1719381) (← links)
- CciMST: a clustering algorithm based on minimum spanning tree and cluster centers (Q1721537) (← links)
- Wasserstein discriminant analysis (Q1722729) (← links)
- Clustering with missing features: a penalized dissimilarity measure based approach (Q1722735) (← links)
- Enhancing the efficiency of a decision support system through the clustering of complex rule-based knowledge bases and modification of the inference algorithm (Q1723092) (← links)
- A new hybrid algorithm for bankruptcy prediction using switching particle swarm optimization and support vector machines (Q1723274) (← links)
- A new method for solving supervised data classification problems (Q1723858) (← links)
- Robustifying sum-product networks (Q1726242) (← links)
- Hierarchical two-part MDL code for multinomial distributions (Q1726276) (← links)
- Granular maximum decision entropy-based monotonic uncertainty measure for attribute reduction (Q1726314) (← links)
- Cost-sensitive feature selection via the \(\ell_{2,1}\)-norm (Q1726316) (← links)
- Cost-sensitive active learning with a label uniform distribution model (Q1726339) (← links)
- A general reduction method for fuzzy objective relation systems (Q1726354) (← links)
- Multi-objective attribute reduction in three-way decision-theoretic rough set model (Q1726359) (← links)
- Multigranulation sequential three-way decisions based on multiple thresholds (Q1726367) (← links)
- Likelihood-fuzzy analysis: from data, through statistics, to interpretable fuzzy classifiers (Q1726378) (← links)
- A novel incremental attribute reduction approach for dynamic incomplete decision systems (Q1726411) (← links)
- An extension of the \(K\)-means algorithm to clustering skewed data (Q1729355) (← links)
- Angle-based twin support vector machine (Q1730466) (← links)
- Bi-criteria optimization problems for decision rules (Q1730539) (← links)
- A fuzzy SV-\(k\)-modes algorithm for clustering categorical data with set-valued attributes (Q1734721) (← links)
- Feature selection for classification models via bilevel optimization (Q1734837) (← links)
- Cost-sensitive feature selection for support vector machines (Q1734839) (← links)
- Regression-aware decompositions (Q1736216) (← links)
- Pattern-guided \(k\)-anonymity (Q1736590) (← links)
- An adaptive spectral clustering algorithm based on the importance of shared nearest neighbors (Q1736648) (← links)
- Affinity propagation clustering using path based similarity (Q1736814) (← links)
- Towards demand side management control using household specific Markovian models (Q1737758) (← links)
- Maximization of AUC and buffered AUC in binary classification (Q1739053) (← links)
- Weight-based label-unknown multi-view data set generation approach (Q1739209) (← links)
- Performance of small-world feedforward neural networks for the diagnosis of diabetes (Q1739963) (← links)
- Learning customized and optimized lists of rules with mathematical programming (Q1741119) (← links)
- Decomposition-by-normalization (DBN): leveraging approximate functional dependencies for efficient CP and Tucker decompositions (Q1741131) (← links)
- Sampling frequent and minimal Boolean patterns: theory and application in classification (Q1741140) (← links)
- Instance-level accuracy versus bag-level accuracy in multi-instance learning (Q1741150) (← links)
