The input table, breast_cancer_data, is assessment data from biopsies of 699 breast tumors. Each tumor is rated on 9 predictor variables, and is classified as either benign (class = 2) or malignant (class = 4). The nine attributes (clumpthickness, uniformityofcellsize, uniformityofcellshape, marginaladhesion, singleepithelialcell, barenuclei, blandchromatin, normalnucleoli, mitoses) are scored on a scale of 1 to 10.
NeuralNet Example Input Table breast_cancer_data (Columns 1-5)
| samplecode |
clumpthickness |
uniformityofcellsize |
uniformityofcellshape |
marginaladhesion |
| 61634 |
5 |
4 |
3 |
1 |
| 63375 |
9 |
1 |
2 |
6 |
| 76389 |
10 |
4 |
7 |
2 |
| 95719 |
6 |
10 |
10 |
10 |
| 128059 |
1 |
1 |
1 |
1 |
| 142932 |
7 |
6 |
10 |
5 |
| 144888 |
8 |
10 |
10 |
8 |
| 145447 |
8 |
4 |
4 |
1 |
| 160296 |
5 |
8 |
8 |
10 |
| 167528 |
4 |
1 |
1 |
1 |
| 169356 |
3 |
1 |
1 |
1 |
| 183913 |
1 |
2 |
2 |
1 |
| ... |
... |
... |
... |
... |
NeuralNet Example Input Table breast_cancer_data (Columns 6-11)
| singleepithelialcell |
barenuclei |
blandchromatin |
normalnucleoli |
mitoses |
class |
| 2 |
|
2 |
3 |
1 |
2 |
| 4 |
10 |
7 |
7 |
2 |
4 |
| 2 |
8 |
6 |
1 |
1 |
4 |
| 8 |
10 |
7 |
10 |
7 |
4 |
| 2 |
5 |
5 |
1 |
1 |
2 |
| 3 |
10 |
9 |
10 |
2 |
4 |
| 5 |
10 |
7 |
8 |
1 |
4 |
| 2 |
9 |
3 |
3 |
1 |
4 |
| 5 |
10 |
8 |
10 |
3 |
4 |
| 2 |
1 |
3 |
6 |
1 |
2 |
| 2 |
|
3 |
1 |
1 |
2 |
| 2 |
1 |
1 |
1 |
1 |
2 |
| ... |
... |
... |
... |
... |
... |