Keywords: مفهوم رانش; Machine learning; Data streams; Concept drift; Supervised learning; Regression; Classification
مقالات ISI مفهوم رانش (ترجمه نشده)
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در صورتی که به ترجمه آماده هر یک از مقالات زیر نیاز داشته باشید، می توانید سفارش دهید تا مترجمان با تجربه این مجموعه در اسرع وقت آن را برای شما ترجمه نمایند.
Keywords: مفهوم رانش; Data streams; Random decision tree; Concept drift; Noisy data
Keywords: مفهوم رانش; Ensemble learning; Learning in changing environments; Regression; Concept drift;
Keywords: مفهوم رانش; Concept drift; Competence model; Case-base maintenance; Incremental supervised learning; Classification
Keywords: مفهوم رانش; Concept drift; Data stream; Online classifier; Ensemble
Keywords: مفهوم رانش; Concept drift; Verification latency; Drift mining;
Keywords: مفهوم رانش; Novel class detection; Data stream; Concept drift; Data stream classification;
Keywords: مفهوم رانش; Concept drift; Data streams; Dynamical systems; Chaos; Unsupervised learning68Q32; 68P20; 68Wxx; 65P20
Keywords: مفهوم رانش; Extreme learning machine; Online/incremental learning; Concept drift; Regularized optimization method
Keywords: مفهوم رانش; Multi-class imbalance; Concept drift; Extreme learning machine; Meta-cognition; Sequential learning
A fog computing based concept drift adaptive process mining framework for mobile APPs
Keywords: مفهوم رانش; Process mining; Concept drift; Fog computing; Log analysis; Cloud governance;
DetectA: abrupt concept drift detection in non-stationary environments
Keywords: مفهوم رانش; Concept drift; Drift detection; Proactive approach;
DRED: An evolutionary diversity generation method for concept drift adaptation in online learning environments
Keywords: مفهوم رانش; Online learning; Concept drift; Evolutionary computation; Diversity;
Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble
Keywords: مفهوم رانش; Dynamic financial distress prediction; Concept drift; Time weighting; Adaboost; Support vector machine;
SOM-based partial labeling of imbalanced data stream
Keywords: مفهوم رانش; Data stream; Concept drift; Self-organizing map (SOM); Support vector machines (SVM); Partial labeling;
RDDM: Reactive drift detection method
Keywords: مفهوم رانش; Concept drift; Drift detection methods; Data stream; Online learning;
DE2: Dynamic ensemble of ensembles for learning nonstationary data
Keywords: مفهوم رانش; Ensemble of ensembles; Growing ensemble; Sparsity learning; Nonstationary environment; Concept drift; Incremental learning;
Adapting a classification rule to local and global shift when only unlabelled data are available
Keywords: مفهوم رانش; Dataset shift; Concept drift; Local drift; Global drift; Verification latency
Early detection of gradual concept drifts by text categorization and Support Vector Machine techniques: The TRIO algorithm
Keywords: مفهوم رانش; Text categorization; Support Vector Machine; Concept drift; Sliding windows; Risky plants; Safety; Early failure detection
RCD: A recurring concept drift framework
Keywords: مفهوم رانش; Data streams; Concept drift; Recurring contexts; On-line learning; Multivariate non-parametric statistical test
Ensemble of online neural networks for non-stationary and imbalanced data streams
Keywords: مفهوم رانش; Data stream classification; Online ensemble; Concept drift; Imbalanced data; Cost-sensitive learning
A rank-one update method for least squares linear discriminant analysis with concept drift
Keywords: مفهوم رانش; Linear discriminant analysis; Least squares solution; Rank-one update; Concept drift
Prediction of members’ return visit rates using a time factor
Keywords: مفهوم رانش; Behavioral targeting; Customer profile; Time function; Concept drift; Return visit rate prediction
An adaptive ensemble classifier for mining concept drifting data streams
Keywords: مفهوم رانش; Adaptive ensembles; Concept drift; Clustering; Data streams; Decision trees; Novel classes
An incremental learning algorithm based on the K-associated graph for non-stationary data classification
Keywords: مفهوم رانش; Graph-based learning; Non-stationary classification; Incremental learning; Concept drift; K-associated graph; Purity measure
Exponentially weighted moving average charts for detecting concept drift
Keywords: مفهوم رانش; Streaming classification; Concept drift; Change detection
Learning from concept drifting data streams with unlabeled data
Keywords: مفهوم رانش; Data stream; Semi-supervised classification; Concept drift; Unlabeled data
A robust incremental learning method for non-stationary environments
Keywords: مفهوم رانش; Incremental learning; Concept drift; Online learning; Neural networks
Class and subclass probability re-estimation to adapt a classifier in the presence of concept drift
Keywords: مفهوم رانش; Changing operational conditions; Concept drift; Imprecise class distribution; Imprecise data distribution; Supervised classification; Posterior probability estimation; Neural networks
Classifying text streams by keywords using classifier ensemble
Keywords: مفهوم رانش; Text stream classification; Concept drift; Classifier ensemble; Knowledge acquisition
Concept drift and how to identify it
Keywords: مفهوم رانش; Concept drift; Semantics; KOS; Ontology change
Transfer estimation of evolving class priors in data stream classification
Keywords: مفهوم رانش; Concept drift; Transfer learning; Prior estimation
Data compression by volume prototypes for streaming data
Keywords: مفهوم رانش; Volume prototypes; One-pass algorithm; Streaming data; Concept drift
Ambiguous decision trees for mining concept-drifting data streams
Keywords: مفهوم رانش; Data streams; Data mining; Concept drift; Ambiguous decision trees; Incremental learning
Managing irrelevant knowledge in CBR models for unsolicited e-mail classification
Keywords: مفهوم رانش; Anti-spam filtering; Irrelevant knowledge; Concept drift; EIRN viewer; CBR system
Mining decision rules on data streams in the presence of concept drifts
Keywords: مفهوم رانش; Data mining; Classification; Decision tree; Data stream; Concept drift
Non-stationary data sequence classification using online class priors estimation
Keywords: مفهوم رانش; Concept drift; Online classification; EM;
Real-time data mining of non-stationary data streams from sensor networks
Keywords: مفهوم رانش; Real-time data mining; Incremental learning; Online learning; Concept drift; Information networks; Traffic sensor networks
An incremental cluster-based approach to spam filtering
Keywords: مفهوم رانش; Email classification; Skewed class distribution; Concept drift; Incremental learning
Info-fuzzy algorithms for mining dynamic data streams
Keywords: مفهوم رانش; Real-time data mining; Data streams; Incremental learning; Online learning; Concept drift; Info-Fuzzy Networks
Dynamic integration of classifiers for handling concept drift
Keywords: مفهوم رانش; Machine learning; Changing environment; Concept drift; Ensemble learning; Dynamic integration of classifiers
Applying lazy learning algorithms to tackle concept drift in spam filtering
Keywords: مفهوم رانش; IBR system; Concept drift; Anti-spam filtering; Model evaluation
Adaptive anomaly detection with evolving connectionist systems
Keywords: مفهوم رانش; Adaptive anomaly detection; Online learning; Concept drift; Evolving connectionist systems; Fuzzy ART; EFuNN
A case-based technique for tracking concept drift in spam filtering
Keywords: مفهوم رانش; Concept drift; Case-based reasoning; Spam filtering;