(self)
| 101 | return best_params |
| 102 | |
| 103 | def adjust_KNearest(self): |
| 104 | print('adjusting KNearest ...') |
| 105 | def f(k): |
| 106 | samples, labels = self.get_dataset() |
| 107 | err = cross_validate(KNearest, dict(k=k), samples, labels) |
| 108 | return k, err |
| 109 | best_err, best_k = np.inf, -1 |
| 110 | for k, err in self.run_jobs(f, xrange(1, 9)): |
| 111 | if err < best_err: |
| 112 | best_err, best_k = err, k |
| 113 | print('k = %d, error: %.2f %%' % (k, err*100)) |
| 114 | best_params = dict(k=best_k) |
| 115 | print('best params:', best_params, 'err: %.2f' % (best_err*100)) |
| 116 | return best_params |
| 117 | |
| 118 | |
| 119 | if __name__ == '__main__': |
no test coverage detected