| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built
(use with caution). | |
| -max-candidates | Maximum number of candidate canopies to retain in memory
at any one time when using canopy clustering.
T2 distance plus, data characteristics,
will determine how many candidate canopies are formed before
periodic and final pruning are performed, which might result
in exceess memory consumption. This setting avoids large numbers
of candidate canopies consuming memory. (default = 100) | |
| A | Distance function to use.
(default: weka.core.EuclideanDistance) | |
| C | Use canopies to reduce the number of distance calculations. | |
| I | Maximum number of iterations. | |
| M | Don't replace missing values with mean/mode. | |
| N | Number of clusters.
(default 2). | |
| O | Preserve order of instances. | |
| S | Random number seed.
(default 10) | |
| V | Display std. deviations for centroids. | |
| W | Full name of clusterer.
(default: weka.clusterers.SimpleKMeans) | default: weka.clusterers.SimpleKMeans |
| fast | Enables faster distance calculations, using cut-off values.
Disables the calculation/output of squared errors/distances. | |
| init | Initialization method to use.
0 = random, 1 = k-means++, 2 = canopy, 3 = farthest first.
(default = 0) | |
| min-density | Minimum canopy density, when using canopy clustering, below which
a canopy will be pruned during periodic pruning. (default = 2 instances) | |
| num-slots | Number of execution slots.
(default 1 - i.e. no parallelism) | |
| output-debug-info | If set, classifier is run in debug mode and
may output additional info to the console | |
| periodic-pruning | How often to prune low density canopies when using canopy clustering.
(default = every 10,000 training instances) | |
| t1 | The T1 distance to use when using canopy clustering. A value < 0 is taken as a
positive multiplier for T2. (default = -1.5) | |
| t2 | The T2 distance to use when using canopy clustering. Values < 0 indicate that
a heuristic based on attribute std. deviation should be used to set this.
(default = -1.0) | |