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CASP-DM: Context Aware Standard Process for Data Mining [article]

Fernando Martínez-Plumed, Lidia Contreras-Ochando, Cèsar Ferri, Peter Flach, José Hernández-Orallo, Meelis Kull, Nicolas Lachiche, María José Ramírez-Quintana
2017 arXiv   pre-print
We propose an extension of the Cross Industry Standard Process for Data Mining (CRISPDM) which addresses specific challenges of machine learning and data mining for context and model reuse handling.  ...  This new general context-aware process model is mapped with CRISP-DM reference model proposing some new or enhanced outputs.  ...  CASP-DM CASP-DM, which stands for Context-Aware Standard Process for Data Mining, is the proposed extension of CRISP-DM for addressing specific challenges of machine learning and data mining for context  ... 
arXiv:1709.09003v1 fatcat:giwxqiy7rbc63bdftzghqnfe2i

Adapting CRISP-DM for Idea Mining

Workneh Y. Ayele
2020 International Journal of Advanced Computer Science and Applications  
The benefits of using standard process models for data mining, such as the de facto and the most popular, Cross-Industry-Standard-Process model for Data Mining (CRISP-DM) are reduced cost and time.  ...  Data mining project managers can benefit from using standard data mining process models.  ...  the Center [1, p.5]. 4 )Healthcare 5 ) 45 Martínez-Plumed et al. adapted CRISP-DM by designing a more flexible and Context-aware Standard Process for Data Mining -(CASP-DM), which inherits flexibility  ... 
doi:10.14569/ijacsa.2020.0110603 fatcat:odmcv6um4vdkpovljdbascecu4

Adapting CRISP-DM for Idea Mining: A Data Mining Process for Generating Ideas Using a Textual Dataset [article]

W. Y. Ayele
2021 arXiv   pre-print
The benefits of using standard process models for data mining, such as the de facto and the most popular, Cross-Industry-Standard-Process model for Data Mining (CRISP-DM) are reduced cost and time.  ...  Data mining project managers can benefit from using standard data mining process models.  ...  Data Mining Process Model 4) Martínez-Plumed et al. adapted CRISP-DM by designing a more flexible and Context-aware Standard Process for Data Mining (CASP-DM), which inherits flexibility and versatility  ... 
arXiv:2105.00574v1 fatcat:go6q4je5wrck7hgqhq32uicz4m

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing [article]

Shailesh Tripathi
2020 arXiv   pre-print
for data mining (CRISP-DM).  ...  The data-driven knowledge discovery framework provides an orderly partition of the data-mining processes to ensure the practical implementation of data analytics and machine learning models.  ...  standard process for data mining (CASP-DM) [72] The deployment context of the model can differ from the training context.  ... 
arXiv:2007.14791v1 fatcat:difcf5l765bvljormncbhh3zca

Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and Manufacturing

Shailesh Tripathi, David Muhr, Manuel Brunner, Herbert Jodlbauer, Matthias Dehmer, Frank Emmert-Streib
2021 Frontiers in Artificial Intelligence  
The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a widely accepted framework in production and manufacturing.  ...  In this paper, we provide a detailed review of CRISP-DM and summarize extensions of this model into a novel framework we call Generalized Cross-Industry Standard Process for Data Science (GCRISP-DS).  ...  goals Context-aware standard process for data mining (CASP-DM) (Martínez-Plumed et al., 2017) (Diez-Olivan et al., 2019) provide a comprehensive review of various methods applied in manufacturing  ... 
doi:10.3389/frai.2021.576892 fatcat:zyf6bk2mhvd2fnoy7hpdhoagtu