Parameters of the K-Means computation method.
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◆ Parameter() [1/5]
Constructs a parameter
- Parameters
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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 |
◆ Parameter() [2/5]
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() [3/5]
Parameter |
( |
DaalContext |
context, |
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long |
nClusters, |
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long |
maxIterations, |
|
|
double |
accuracyThreshold, |
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double |
gamma |
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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 |
◆ Parameter() [4/5]
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 |
◆ Parameter() [5/5]
Constructs a parameter
- Parameters
-
context | Context to manage the parameter of the K-Means algorithm |
nClusters | Number of clusters |
maxIterations | Number of iterations |
◆ getAccuracyThreshold()
double getAccuracyThreshold |
( |
| ) |
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Retrieves the threshold for the termination of the algorithm
- Returns
- Threshold for the termination of the algorithm
◆ getAssignFlag()
boolean getAssignFlag |
( |
| ) |
|
Retrieves the flag for the assignment of data points
- Returns
- Flag for the assignment of data points
◆ getDistanceType()
Returns the distance type
- Returns
- Distance type
◆ getGamma()
Retrieves the weight used in distance calculation for categorical features
- Returns
- Weight used in distance calculation for categorical features
◆ getMaxIterations()
long getMaxIterations |
( |
| ) |
|
Retrieves the number of iterations
- Returns
- Number of iterations
◆ getNClusters()
Retrieves the number of clusters
- Returns
- Number of clusters
◆ setAccuracyThreshold()
void setAccuracyThreshold |
( |
double |
accuracy | ) |
|
Sets the threshold for the termination of the algorithm
- Parameters
-
accuracy | Threshold for the termination of the algorithm |
◆ setAssignFlag()
void setAssignFlag |
( |
boolean |
assignFlag | ) |
|
Sets the flag for the assignment of data points
- Parameters
-
assignFlag | Flag to enable assignment of observations to clusters |
◆ setGamma()
void setGamma |
( |
double |
gamma | ) |
|
Sets the weight used in distance calculation for categorical features
- Parameters
-
gamma | Weight used in distance calculation for categorical features |
◆ setMaxIterations()
void setMaxIterations |
( |
long |
max | ) |
|
Sets the number of iterations
- Parameters
-
◆ setNClusters()
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: