Supervised Temporal Classification Task

A Supervised Temporal Classification Task is a supervised IID classification task that is a temporal classification task.

• Context:
  • Input:
    • …
  • It can range from being a Fully-Supervised Temporal Classification Task to being a Semi-Supervised Temporal Classification Task, depending on the presence of unlabeled learning records.
  • It can range from being a Ranking Supervised Temporal Classification Task to being a Probabilistic Supervised Temporal Classification Task, depending on the requirement for a probability value.
  • It can range from being a Supervised Two-Class Temporal Classification Task to being a Supervised Multi-Class Temporal Classification Task, depending on the class set size.
  • It can range from being a Univariate Supervised Temporal Classification Task to being a Multivariate Supervised Temporal Classification Task, depending on the feature set size.
  • It can range from being a Supervised One-Label Temporal Classification Task to being a Supervised Multi-Label Temporal Classification Task, depending on the number of class labels to predict.
  • It can range from being an Online Supervised Temporal Classification Task to being an Offline Supervised Temporal Classification Task, depending on the incremental availability of data.
  • It can range from being a Model-based Supervised Temporal Classification Task to being an Model-free Supervised Temporal Classification Task, depending on the requirement of a classification model.
  • It can be solved by a Supervised Temporal Classification System and implements a Supervised Temporal Classification Algorithm.
• Example(s):
  • Supervised Temporal Text-Item Classification.
  • Supervised Recommendation.
  • …
• Counter-Example(s):
  • Supervised Temporal Estimation.
• See: Supervised Forecasting, Supervised Ranking.

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References

2012

• (Graves, 2012) ⇒ Alex Graves. (2012). “Supervised Sequence Labelling.” In: Supervised Sequence Labelling with Recurrent Neural Networks, pp. 5-13 . Springer Berlin Heidelberg,

2006

• (Wei & Keogh, 2006) ⇒ Li Wei, and Eamonn Keogh. (2006). “Semi-supervised Time Series Classification.” In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge discovery and data mining.

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