Supervised Learning System Performance Evaluation Task

AKA: Empirical Evaluation.
Context:
- Input:
  - an Supervised Learning Systems.
  - a Training Record Set.
  - a Testing Record Set.
- output: a Performance Analysis Report.
Example(s):
- Estimate a Predictive Function's Accuracy (Accuracy Estimation Task)..
See: Algorithm Complexity Analysis Task, Model Assessment Task.

References

(Jin et al., 2009) ⇒ Wei Jin, Hung Hay Ho, Rohini K Srihari. (2009). “OpinionMiner: A Novel Machine Learning System for Web Opinion Mining and Extraction.” In: Proceedings of ACM SIGKDD Conference (KDD-2009). doi:10.1145/1557019.1557148.
- In this paper, we describe the architecture and main components of the system. The evaluation of the proposed method is presented based on processing the online product reviews from Amazon and other publicly available datasets.

(Yang & Liu, 1999) ⇒ Yiming Yang, and Xin Liu. (1999). “A Re-examination of Text Categorization Methods.” In: Proceedings of the 22nd ACM SIGIR Conference Retrieval (SIGIR 1999).
- In this paper we presented a controlled study with significance analyses on five well-known text categorization methods.
(Goldberg, 1999) ⇒ Andrew V. Goldberg. (1999). “Selecting Problems for Algorithm Evaluation.” In: Algorithm Engineering. Springer. doi:10.1007/3-540-48318-7_1
- ABSTRACT: In this paper we address the issue of developing test sets for computational evaluation of algorithms. We discuss both test families for comparing several algorithms and selecting one to use in an application, and test families for predicting algorithm performance in practice.