Cancer Cell Detection using Support Vector Machine
We use Support Vector Machine(SVM) to build and train a model using human cell records, and classify cells to whether the samples are benign or malignant.
The example is based on a dataset that is publicly available from the UCI Machine Learning Repository (Asuncion and Newman, 2007)[http://mlearn.ics.uci.edu/MLRepository.html]. The dataset consists of several hundred human cell sample records, each of which contains the values of a set of cell characteristics. The fields in each record are:
| Field name | Description |
|---|---|
| ID | Clump thickness |
| Clump | Clump thickness |
| UnifSize | Uniformity of cell size |
| UnifShape | Uniformity of cell shape |
| MargAdh | Marginal adhesion |
| SingEpiSize | Single epithelial cell size |
| BareNuc | Bare nuclei |
| BlandChrom | Bland chromatin |
| NormNucl | Normal nucleoli |
| Mit | Mitoses |
| Class | Benign or malignant |