Parameters of the K-Means computation method.
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Constructs a parameter
- Parameters
-
| context | Context to manage the parameter of the K-Means algorithm |
| nClusters | Number of clusters |
| maxIterations | Number of iterations |
| accuracyThreshold | Threshold for the termination of the algorithm |
| gamma | Weight used in distance calculation for categorical features |
| distanceType | Distance used in the algorithm |
| assignFlag | Flag to enable assignment of observations to clusters; assigns data points |
Constructs a parameter
- Parameters
-
| context | Context to manage the parameter of the K-Means algorithm |
| nClusters | Number of clusters |
| maxIterations | Number of iterations |
| accuracyThreshold | Threshold for the termination of the algorithm |
| gamma | Weight used in distance calculation for categorical features |
| distanceType | Distance used in the algorithm |
| Parameter |
( |
DaalContext |
context, |
|
|
long |
nClusters, |
|
|
long |
maxIterations, |
|
|
double |
accuracyThreshold, |
|
|
double |
gamma |
|
) |
| |
Constructs a parameter
- Parameters
-
| context | Context to manage the parameter of the K-Means algorithm |
| nClusters | Number of clusters |
| maxIterations | Number of iterations |
| accuracyThreshold | Threshold for the termination of the algorithm |
| gamma | Weight used in distance calculation for categorical features |
Constructs a parameter
- Parameters
-
| context | Context to manage the parameter of the K-Means algorithm |
| nClusters | Number of clusters |
| maxIterations | Number of iterations |
| accuracyThreshold | Threshold for the termination of the algorithm |
Constructs a parameter
- Parameters
-
| context | Context to manage the parameter of the K-Means algorithm |
| nClusters | Number of clusters |
| maxIterations | Number of iterations |
| double getAccuracyThreshold |
( |
| ) |
|
Retrieves the threshold for the termination of the algorithm
- Returns
- Threshold for the termination of the algorithm
| boolean getAssignFlag |
( |
| ) |
|
Retrieves the flag for the assignment of data points
- Returns
- Flag for the assignment of data points
Returns the distance type
- Returns
- Distance type
Retrieves the weight used in distance calculation for categorical features
- Returns
- Weight used in distance calculation for categorical features
| long getMaxIterations |
( |
| ) |
|
Retrieves the number of iterations
- Returns
- Number of iterations
Retrieves the number of clusters
- Returns
- Number of clusters
| void setAccuracyThreshold |
( |
double |
accuracy | ) |
|
Sets the threshold for the termination of the algorithm
- Parameters
-
| accuracy | Threshold for the termination of the algorithm |
| void setAssignFlag |
( |
boolean |
assignFlag | ) |
|
Sets the flag for the assignment of data points
- Parameters
-
| assignFlag | Flag to enable assignment of observations to clusters |
| void setGamma |
( |
double |
gamma | ) |
|
Sets the weight used in distance calculation for categorical features
- Parameters
-
| gamma | Weight used in distance calculation for categorical features |
| void setMaxIterations |
( |
long |
max | ) |
|
Sets the number of iterations
- Parameters
-
| void setNClusters |
( |
long |
nClusters | ) |
|
Sets the number of clusters
- Parameters
-
| nClusters | Number of clusters |
The documentation for this class was generated from the following file: