Evolving Data Streams
Activity Recognition with Evolving Data Streams: A Review
... along evolving data ...initial data represents a set of activities that is collected to train the primitive ...training data [Yang et ...sensory data for all kind of activities that ...
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Classification of evolving data streams with infinitely delayed labels
... of evolving data streams classification algorithms assume that the actual labels of the predicted examples are readily available without any time delay just after a prediction is ...in data ...
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Clustering based active learning for evolving data streams
... Abstract. Data labeling is an expensive and time-consuming ...the data stream ...for evolving data streams based on a pre-clustering step, for selecting the most informative instances ...
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Improving adaptive bagging methods for evolving data streams
... In [6] two new state-of-the-art bagging methods were presented: ASHT Bag- ging using trees of different sizes, and ADWIN Bagging using a change detector to decide when to discard underperforming ensemble members. This ...
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Adaptive XML Tree Classification on Evolving Data Streams
... Abstract. We propose a new method to classify patterns, using closed and maximal frequent patterns as features. Generally, classification re- quires a previous mapping from the patterns to classify to vectors of features, ...
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Fully online clustering of evolving data streams into arbitrarily shaped clusters
... In this paper we present a fully online technique for clustering evolving data streams into arbitrary shaped clusters. It is a two stage technique that is accurate, robust to noise, computationally ...
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Fully online clustering of evolving data streams into arbitrarily shaped clusters
... in data availability in continuous data streams and clustering of this data has many advantages in data analy- ...these data streams are not stationary, but evolve over ...
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An Approach for Mining Frequent Item sets from Tuple evolving Data Streams
... Today, data streaming applications consider every incoming transaction as a new ...the streams over the time. This kind of revision in data streaming application gives new and hidden knowledge, also ...
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Clustering Over Multiple Evolving Data Streams of the Traffic Cyber-Physical Systems
... multiple data streams of the traffic Cyber-Physical Systems (CPS) has been attracted an increasing amount of attentions by the related ...sensor data streams by low rank approximation Matrix ...
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AnyNovel: detection of novel concepts in evolving data streams: An application for activity recognition
... A data stream is a flow of unbounded data that arrives continu- ously at high ...the data changes over the time while stream evolves. The evolving nature of data causes essen- tially ...
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Unsupervised tracking of time-evolving data streams and an application to short-term urban traffic flow forecasting
... Chapter 3 provides a detailed description of relevant issues of the clustering methods for data streams. Then describes the Graded Possibilistic c Means (GPCM) clustering method [84] and the followed ...
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Change detection in categorical evolving data streams
... This means that, each time, the model previously learnt is discarded and replaced with a new one while CDCStream adopts a different strategy, and it adapts itself to the value of batch size in order to discover changes. ...
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New Ensemble Methods For Evolving Data Streams
... of data streams is quickly becoming a key area of data mining research as the number of applica- tions demanding such processing ...such data streams evolve over time, that is when con- ...
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An Ensemble Classification Framework to Evolving Data Streams
... big data analysis is analysis of data mining and techniques ...of data, estimating the relevant information satisfying the user query is a challenging ...task. Data prediction, Extraction and ...
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Efficient multi-label classification for evolving data streams
... in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and ...multi-label evolving stream classification, and new efficient methods that ...
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Cloud-Based Malware Detection for Evolving Data Streams
... static data segments, headers, and all other content of untrusted ...and data tables, capture important low-level structural details that are often abstracted away by higher- level ...
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Scalable and efficient multi-label classification for evolving data streams
... – data may be evolving over time; and – expect an infinite stream, but process it under finite resources (time and ...example data stream applications above can be applied to multi-label contexts, ...
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Adaptive parameter-free learning from evolving data streams
... Most strategies for dealing with time change contain hardwired constants, or else require input parameters, con- cerning the expected speed or frequency of the change; some examples are a priori definitions of sliding ...
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Learning from evolving data streams: online triage of bug reports
... the evolving data stream and incremen- tally update the model after each data ...the data sets which we col- lected and used, in both their raw and prepro- cessed ...
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Improving decision tree and neural network learning for evolving data-streams
... of data im- poses serious challenges. First, given the vast amount of data arriving, storing it before the processing step is not ...collecting data for long enough periods the relations or patterns ...
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