Neural Network: Breast Cancer Data Set

 

For each study the general procedure is to:
Review theoretical background based on available resources in the course content
Describe , process and use the Breast Cancer Dataset

” Run an analysis, perform evaluation, and capture the results
” Document your findings and analysis in a data mining analytical report

Submit your analysis report by addressing the following critical areas:

” Introduction: give some background and context about the domain of application, provide the rationale for the type of analysis, and state the objective clearly.

” Analysis: describe the data both qualitatively and quantitatively through exploratory analysis, perform necessary preprocessing activities, give some intuition about the algorithm and core parameters, demonstrate the model building steps along with parameter tuning, and explain all your assumptions.

” Result: explain the result and interpret the model output using terms that reflect the application area, perform model evaluation using the appropriate metrics, and leverage visualization.

” Conclusion: summarize your main findings, discuss experimental limitations related to the data and/or implementation of the algorithm, and suggest improvement areas as a potential future work.

Client:
okay the code works but doesn’t match the paper or the analysis at all.
everything in the paper the graphics dont match
the code doesnt match what was in the paper
what does the R code tell me about the data
what does the neural network tell me about the data? and the code produces the graphics for the paper
where did those graphics come from that are in the paper?