Pages that link to "Item:Q1394785"
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The following pages link to Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy (Q1394785):
Displaying 50 items.
- Ensemble classification based on generalized additive models (Q151094) (← links)
- Bagging binary and quantile predictors for time series (Q291866) (← links)
- Training regression ensembles by sequential target correction and resampling (Q454845) (← links)
- Ectropy of diversity measures for populations in Euclidean space (Q545352) (← links)
- Greedy optimization classifiers ensemble based on diversity (Q632627) (← links)
- CE-PLoc: An ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition (Q647294) (← links)
- Majority vote ensembles of conformal predictors (Q669293) (← links)
- From cluster ensemble to structure ensemble (Q712663) (← links)
- Hybrid cluster ensemble framework based on the random combination of data transformation operators (Q763364) (← links)
- An analysis of diversity measures (Q851877) (← links)
- A cooperative constructive method for neural networks for pattern recognition (Q853100) (← links)
- An improved BioHashing for human authentication (Q856473) (← links)
- Pairwise fusion matrix for combining classifiers (Q882250) (← links)
- Pruning of error correcting output codes by optimization of accuracy-diversity trade off (Q890296) (← links)
- A lazy bagging approach to classification (Q936407) (← links)
- A dynamic overproduce-and-choose strategy for the selection of classifier ensembles (Q936409) (← links)
- Collective-agreement-based pruning of ensembles (Q961226) (← links)
- Taxonomy for characterizing ensemble methods in classification tasks: a review and annotated bibliography (Q961895) (← links)
- Iterative Boolean combination of classifiers in the ROC space: an application to anomaly detection with HMMs (Q975181) (← links)
- Information theoretic combination of pattern classifiers (Q991948) (← links)
- EROS: Ensemble rough subspaces (Q996469) (← links)
- Consensus fingerprint matching with genetically optimised approach (Q1015208) (← links)
- Negative correlation in incremental learning (Q1024030) (← links)
- Methods and algorithms of collective recognition (Q1027647) (← links)
- Decision-level fusion in fingerprint verification (Q1347726) (← links)
- Vote counting measures for ensemble classifiers. (Q1425964) (← links)
- Distant diversity in dynamic class prediction (Q1639212) (← links)
- Dynamic classifier aggregation using interaction-sensitive fuzzy measures (Q1677625) (← links)
- Context-based unsupervised ensemble learning and feature ranking (Q1689607) (← links)
- Improving bagging performance through multi-algorithm ensembles (Q1762211) (← links)
- Exploiting unlabeled data to enhance ensemble diversity (Q1944971) (← links)
- Comparing apples and oranges: measuring differences between exploratory data mining results (Q1944984) (← links)
- Rotation Forests for regression (Q2016344) (← links)
- Forecasting corporate failure using ensemble of self-organizing neural networks (Q2028771) (← links)
- Random sampling accelerator for attribute reduction (Q2069052) (← links)
- A distributed ensemble of relevance vector machines for large-scale data sets on Spark (Q2098338) (← links)
- Forecast with forecasts: diversity matters (Q2140152) (← links)
- A weighted multiple classifier framework based on random projection (Q2214960) (← links)
- A probabilistic classifier ensemble weighting scheme based on cross-validated accuracy estimates (Q2218385) (← links)
- Forecasting bankruptcy using biclustering and neural network-based ensembles (Q2241078) (← links)
- On the discovery of events in EEG data utilizing information fusion (Q2255754) (← links)
- Canonical forest (Q2259759) (← links)
- Selective ensemble of SVDDs with Renyi entropy based diversity measure (Q2289595) (← links)
- Using diversity of errors for selecting members of a committee classifier (Q2369591) (← links)
- The combination of multiple classifiers using an evidential reasoning approach (Q2389681) (← links)
- The random electrode selection ensemble for EEG signal classification (Q2476577) (← links)
- From dynamic classifier selection to dynamic ensemble selection (Q2476581) (← links)
- Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification (Q2660967) (← links)
- An extension of the \(Q\) diversity metric for information processing in multiple classifier systems: a field evaluation (Q2867974) (← links)
- Diversity measures in ensemble learning (Q2924521) (← links)
