Lit Review
ABE is good for prediction especially when different data types are used.
Build clusters. Assign new project to one of the aforementioned clusters
Effort Estimation Using Analogy
When compared with regression and step-wise estimates, analogy performed with superior accuracy, and had the advantage of being self calibrating. In being an accurate predictor, estimation by analogy should become one of the techniques considered for estimation in the early stage of development. When using several different estimation techniques, the variance in predictions can also be used as a risk indicator.
1. How best to describe projects
2. Measure similarity, and how much confidence
3. How do we use known effort values to drive estimate (means/weighted means/etc.
Differing datasets
I sit in such fear. Trapped by not caring. Not having incentive. I need to spend time remembering why I am doing what I do everyday. And the why is hard when you don't care about....anything. The why can be so simple, short-term, long-term, for me, myself, I, friends, family, the world. Learn to relax the mind.
An optimized Analogy-Based Project Effort Estimation
Find appropriate # of closest projects (# of analogies)
Which adjustment technique
Conclusions: # of analogies was remarkably variable for each test project
Mohammad Azzeh, Yousef Elsheikh and Marwan Alseid, “An Optimized Analogy-Based Project Effort Estimation” International Journal of Advanced Computer Science and Applications(IJACSA), 5(4), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050402 - See more at: http://thesai.org/Publications/ViewPaper?Volume=5&Issue=4&Code=IJACSA&SerialNo=2#sthash.EDi2Xwra.dpuf
Build clusters. Assign new project to one of the aforementioned clusters
Effort Estimation Using Analogy
Shepperd, Schofield, Kitchenham : ”Effort Estimation Using Analogy” , Proceedings ICSE.18 (1996) 170-178
When compared with regression and step-wise estimates, analogy performed with superior accuracy, and had the advantage of being self calibrating. In being an accurate predictor, estimation by analogy should become one of the techniques considered for estimation in the early stage of development. When using several different estimation techniques, the variance in predictions can also be used as a risk indicator.
1. How best to describe projects
2. Measure similarity, and how much confidence
3. How do we use known effort values to drive estimate (means/weighted means/etc.
Differing datasets
- Number of observations
- Number of variables
I sit in such fear. Trapped by not caring. Not having incentive. I need to spend time remembering why I am doing what I do everyday. And the why is hard when you don't care about....anything. The why can be so simple, short-term, long-term, for me, myself, I, friends, family, the world. Learn to relax the mind.
An optimized Analogy-Based Project Effort Estimation
Find appropriate # of closest projects (# of analogies)
Which adjustment technique
Conclusions: # of analogies was remarkably variable for each test project
Mohammad Azzeh, Yousef Elsheikh and Marwan Alseid, “An Optimized Analogy-Based Project Effort Estimation” International Journal of Advanced Computer Science and Applications(IJACSA), 5(4), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050402 - See more at: http://thesai.org/Publications/ViewPaper?Volume=5&Issue=4&Code=IJACSA&SerialNo=2#sthash.EDi2Xwra.dpuf
Dataset Quality Assessment: An extension for analogy based effort estimation
ASSUMPTION: Similar projects in terms of attribute values will also be similar in terms of effort values.
Kendall row wise correlation : able to provide statistical evidence for attribute subset selection, statistical mechanism for identification of abnormal projects within a dataset, able to assess relevancy of nominal(categorical) attributes individually
APA
Azzeh, M. (2013). Dataset quality assessment: An extension for analogy based effort estimation. International Journal of Computer Science and Engineering Survey, 4, 1-21.
MLA
Azzeh, Mohammad. "Dataset Quality Assessment: An Extension for Analogy Based Effort Estimation." International Journal of Computer Science and Engineering Survey, 4 (2013): 1-21.
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