<abstract xmlns="http://www.w3.org/1999/xhtml">Artificial Intelligence is used in business through machine learning algorithms. Machine learning is a part of computer science focused on computer systems learning to perform a specific task without using explicit instructions, relying on patterns and inference instead.Though it might seem like we’ve come a long way in the last ten years, which is true from a research perspective, the adoption of AI among corporations is still relatively low. Over time it became possible to automate more tasks and business processes than ever before. The benefit of using artificial intelligence is that does not require to program every step of the process, predicting at each step what could happen and how to resolve it. The algorithms decide for themselves in each case how the problems should be solved, based on the data that is used.I apply Python language to create a synthetic feature vector that allows visualizations in two dimensions for EDIBTA financial ratio. I use Mean-Square Error in order to evaluate the success, having the optimal parameters. In this section, I also mentioned about the purpose, goals, and applications of cluster analysis. I indicated about the basics of cluster analysis and how to do it and also did a demonstration on how to use K-Means.</abstract>

Artificial Intelligence is used in business through machine learning algorithms. Machine learning is a part of computer science focused on computer systems learning to perform a specific task without using explicit instructions, relying on patterns and inference instead.Though it might seem like we’ve come a long way in the last ten years, which is true from a research perspective, the adoption of AI among corporations is still relatively low. Over time it became possible to automate more tasks and business processes than ever before. The benefit of using artificial intelligence is that does not require to program every step of the process, predicting at each step what could happen and how to resolve it. The algorithms decide for themselves in each case how the problems should be solved, based on the data that is used.I apply Python language to create a synthetic feature vector that allows visualizations in two dimensions for EDIBTA financial ratio. I use Mean-Square Error in order to evaluate the success, having the optimal parameters. In this section, I also mentioned about the purpose, goals, and applications of cluster analysis. I indicated about the basics of cluster analysis and how to do it and also did a demonstration on how to use K-Means.

Combining Regression and Clustering for Financial Analysis

Proceedings of the International Conference on Applied Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Combining Regression and Clustering for Financial Analysis"}

Artificial Intelligence is used in business through machine learning algorithms. Machine learning is a part of computer science focused on computer systems...

Combining Regression and Clustering for Financial Analysis

Online veröffentlicht: 31. Mai 2021

Seitenbereich: 77 - 86

DOI: https://doi.org/10.2478/icas-2021-0007

Schlüsselwörter
artificial intelligence, machine learning, data mining, OLS regression, applied statistics

© 2021 Andreea Ioana Chiriac, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Combining Regression and Clustering for Financial Analysis

Online veröffentlicht: 31. Mai 2021

Seitenbereich: 77 - 86

DOI: https://doi.org/10.2478/icas-2021-0007

Schlüsselwörterartificial intelligence, machine learning, data mining, OLS regression, applied statistics

© 2021 Andreea Ioana Chiriac, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
artificial intelligence, machine learning, data mining, OLS regression, applied statistics