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Abstract

no more than 300 words that describes the data set and your work with it

This is a UCI data set last updated in 1992 about breast cancer. 699 patients' information about their breast tumors was recorded. There are 10 attributes: sample ID number, clump thickness, cell size uniformity, cell shape uniformity, marginal adhesion, single epithelial cell size, bare nuclei,bland chromatin, normal nucleoli, mitoses, and class (2 for benign, 4 for malignant). The cell information is on a scale of 1-10 otherwise. I am going to look at the relationship between various attributes and see if we can predict which cells are cancerous.

Problem Statement

clearly describing the data set, its source, and the main problems for which you are developing data analyses and visualizations.

Methods

describe the visualization and analysis tools/methods you used

Results

show the visualizations and analysis results

Conclusion

highlights the important results and concludes the writeup

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