Spam Classifier Visualization
This explorer compares perceptron, decision tree, and support vector machine classifiers on a two-feature email dataset.
Decision Boundary Visualization
Not spam32class 0
Spam68class 1
Perceptron accuracy100.0%RMSE 12.0874
Decision tree100.0%RMSE 0.0000
SVM94.0%RMSE 0.7770
Dataset Preview
| Email Length (words) | Keyword Count | Class |
|---|---|---|
| 81.16 | 1.00 | Not Spam |
| 190.64 | 13.00 | Spam |
| 149.08 | 6.00 | Spam |
| 123.75 | 10.00 | Spam |
| 39.64 | 18.00 | Spam |
| 39.64 | 5.00 | Not Spam |
| 21.04 | 8.00 | Not Spam |
| 174.57 | 15.00 | Spam |
| 13.91 | 6.00 | Not Spam |
| 194.28 | 3.00 | Spam |
Perceptron Status
Epochs run1260 errors in final epoch
Weight 10.0838Email Length (words)
Weight 21.6462Keyword Count
Bias-18.3700boundary offset
Decision function: f(x) = 0.084 * x1 + 1.646 * x2 + -18.370. If f(x) >= 0, predict spam.
Training History
| Epoch | Errors | Weight 1 | Weight 2 | Bias | Delta W1 | Delta W2 | Delta Bias | Status |
|---|---|---|---|---|---|---|---|---|
| 115 | 26 | 0.208585 | 1.546174 | -16.980000 | +0.135347 | -0.010000 | -0.120000 | 26 errors |
| 116 | 36 | 0.227634 | 1.636174 | -17.140000 | +0.019049 | +0.090000 | -0.160000 | 36 errors |
| 117 | 35 | 0.300225 | 1.696174 | -17.290000 | +0.072591 | +0.060000 | -0.150000 | 35 errors |
| 118 | 35 | 0.372816 | 1.756174 | -17.440000 | +0.072591 | +0.060000 | -0.150000 | 35 errors |
| 119 | 34 | 0.307582 | 1.846174 | -17.580000 | -0.065234 | +0.090000 | -0.140000 | 34 errors |
| 120 | 33 | 0.342334 | 1.776174 | -17.730000 | +0.034751 | -0.070000 | -0.150000 | 33 errors |
| 121 | 30 | 0.264972 | 1.706174 | -17.870000 | -0.077361 | -0.070000 | -0.140000 | 30 errors |
| 122 | 35 | 0.337563 | 1.766174 | -18.020000 | +0.072591 | +0.060000 | -0.150000 | 35 errors |
| 123 | 27 | 0.095041 | 1.636174 | -18.150000 | -0.242522 | -0.130000 | -0.130000 | 27 errors |
| 124 | 26 | 0.230388 | 1.626174 | -18.270000 | +0.135347 | -0.010000 | -0.120000 | 26 errors |
| 125 | 22 | 0.083804 | 1.646174 | -18.370000 | -0.146584 | +0.020000 | -0.100000 | 22 errors |
| 126 | 0 | 0.083804 | 1.646174 | -18.370000 | +0.000000 | +0.000000 | +0.000000 | Converged |
Showing the latest 12 rows of 127 total training states.
Recent Perceptron Update
The latest epoch made no mistakes, so no weight update was needed.
Decision Tree Details
Depth3maximum rule depth
Leaves5terminal predictions
Nodes9total tree nodes
|--- Keyword Count <= 6.50 | |--- Email Length (words) <= 142.48 | | |--- class: 0 value: [26, 0] | |--- Email Length (words) > 142.48 | | |--- class: 1 value: [0, 10] |--- Keyword Count > 6.50 | |--- Email Length (words) <= 29.89 | | |--- Keyword Count <= 14.00 | | | |--- class: 0 value: [6, 0] | | |--- Keyword Count > 14.00 | | | |--- class: 1 value: [0, 2] | |--- Email Length (words) > 29.89 | | |--- class: 1 value: [0, 56]
SVM Details
KernelLINEARimplemented locally
C1.0regularization
Support vectors2424.0% of data
Gamma0.00013scale value
| ID | Email Length (words) | Keyword Count |
|---|---|---|
| 0 | 39.64 | 18.00 |
| 1 | 50.34 | 16.00 |
| 2 | 44.55 | 13.00 |
| 3 | 44.85 | 17.00 |
| 4 | 109.70 | 4.00 |
| 5 | 36.50 | 18.00 |
| 6 | 96.65 | 5.00 |
| 7 | 47.94 | 16.00 |
| 8 | 122.56 | 0.00 |
| 9 | 33.19 | 19.00 |
| 10 | 135.88 | 1.00 |
| 11 | 69.23 | 12.00 |