1. Research Topic: Super Computer Data Mining
The aim of this project is to produce a super-computing data mining resource for use by the UK academic community which utilizes a number of advanced machine learning and statistical algorithms for large datasets. In particular, a number of evolutionary computing-based algorithms and the ensemble machine approach will be used to exploit the large-scale parallelism possible in super-computing. This purpose is embodied in the following objectives:
1. to develop a massively parallel approach for commonly used statistical and machine learning techniques for exploratory data analysis
1. to develop a massively parallel approach to the use of evolutionary computing techniques for feature creation and selection
1. to develop a massively parallel approach to the use of evolutionary computing techniques for data modelling
1. to develop a massively parallel approach to the use of ensemble machines for data modelling consisting of many well-known machine learning algorithms;
1. to develop an appropriate super-computing infra-structure to support the use of such advanced machine learning techniques with large datasets.
Research Needs:
Problem definition – In the first phase problem definition is listed i.e. business aims and objectives are determined taking into consideration certain factors like the current background and future prospective.
Data exploration – Required data is collected and explored using various statistical methods along with identification of underlying problems.
Data preparation – The data is prepared for modeling by cleansing and formatting the raw data in the desired way. The meaning of data is not changed while preparing.
Modeling – In this phase the data model is created by applying certain mathematical functions and modeling techniques. After the model is created it goes through validation and verification.
Evaluation – After the model is created, it is evaluated by a team of experts to check whether it satisfies business objectives or not.
Deployment – After evaluation, the model is deployed and further plans are made for its maintenance. A properly organized report is prepared with the summary of the work done.
Research paper Policy
· APA format
. https://apastyle.apa.org/
. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
· Min number of pages are 15 pages
· Must have
. Contents with page numbers
. Abstract
. Introduction
. The problem
4. Are there any sub-problems?
4. Is there any issue need to be present concerning the problem?
. The solutions
5. Steps of the solutions
. Compare the solution to other solution
. Any suggestion to improve the solution
. Conclusion
. References
· Missing one of the above will result -5/30 of the research paper
· Paper does not stick to the APA will result in 0 in the research paper
· Submission
. you have multiple submission to check you safe assignments
. The percentage accepted is 1%.
1. Research Topic Super Computer Data MiningThe aim of this.docx
1. 1. Research Topic: Super Computer Data Mining
The aim of this project is to produce a super-computing data
mining resource for use by the UK academic community which
utilizes a number of advanced machine learning and statistical
algorithms for large datasets. In particular, a number of
evolutionary computing-based algorithms and the ensemble
machine approach will be used to exploit the large-scale
parallelism possible in super-computing. This purpose is
embodied in the following objectives:
1. to develop a massively parallel approach for commonly used
statistical and machine learning techniques for exploratory data
analysis
1. to develop a massively parallel approach to the use of
evolutionary computing techniques for feature creation and
selection
1. to develop a massively parallel approach to the use of
evolutionary computing techniques for data modelling
1. to develop a massively parallel approach to the use of
ensemble machines for data modelling consisting of many well-
known machine learning algorithms;
1. to develop an appropriate super-computing infra-structure to
support the use of such advanced machine learning techniques
with large datasets.
Research Needs:
Problem definition – In the first phase problem definition is
listed i.e. business aims and objectives are determined taking
into consideration certain factors like the current background
and future prospective.
Data exploration – Required data is collected and explored
using various statistical methods along with identification of
underlying problems.
Data preparation – The data is prepared for modeling by
2. cleansing and formatting the raw data in the desired way. The
meaning of data is not changed while preparing.
Modeling – In this phase the data model is created by applying
certain mathematical functions and modeling techniques. After
the model is created it goes through validation and verification.
Evaluation – After the model is created, it is evaluated by a
team of experts to check whether it satisfies business objectives
or not.
Deployment – After evaluation, the model is deployed and
further plans are made for its maintenance. A properly
organized report is prepared with the summary of the work
done.
Research paper Policy
· APA format
. https://apastyle.apa.org/
.
https://owl.purdue.edu/owl/research_and_citation/apa_style/apa
_formatting_and_style_guide/general_format.html
· Min number of pages are 15 pages
· Must have
. Contents with page numbers
. Abstract
. Introduction
. The problem
4. Are there any sub-problems?
4. Is there any issue need to be present concerning the problem?
. The solutions
5. Steps of the solutions
. Compare the solution to other solution
. Any suggestion to improve the solution
. Conclusion
. References
· Missing one of the above will result -5/30 of the research
paper
· Paper does not stick to the APA will result in 0 in the research