A set of results returned by Kinetica.aggregateKMeans(string,IList<string>,int,double,IDictionary<string, string>). More...
Inheritance diagram for kinetica.AggregateKMeansResponse:
Collaboration diagram for kinetica.AggregateKMeansResponse:
Properties | |
| IList< IList< double > > | means [get, set] |
| The k-mean values found. More... | |
| IList< long > | counts = new List<IList<double>>() [get, set] |
| The number of elements in the cluster closest the corresponding k-means values. More... | |
| IList< double > | rms_dists = new List<long>() [get, set] |
| The root mean squared distance of the elements in the cluster for each of the k-means values. More... | |
| long | count = new List<double>() [get, set] |
| The total count of all the clusters - will be the size of the input table. More... | |
| double | rms_dist [get, set] |
| The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize. More... | |
| double | tolerance [get, set] |
| The distance between the last two iterations of the algorithm before it quit. More... | |
| int | num_iters [get, set] |
| The number of iterations the algorithm executed before it quit. More... | |
| Properties inherited from kinetica.KineticaData | |
| Schema | Schema [get] |
| Avro Schema for this class More... | |
Additional Inherited Members | |
| Public Member Functions inherited from kinetica.KineticaData | |
| KineticaData (KineticaType type) | |
| Constructor from Kinetica Type More... | |
| KineticaData (System.Type type=null) | |
| Default constructor, with optional System.Type More... | |
| object | Get (int fieldPos) |
| Retrieve a specific property from this object More... | |
| void | Put (int fieldPos, object fieldValue) |
| Write a specific property to this object More... | |
| Static Public Member Functions inherited from kinetica.KineticaData | |
| static RecordSchema | SchemaFromType (System.Type t, KineticaType ktype=null) |
| Create an Avro Schema from a System.Type and a KineticaType. More... | |
Detailed Description
A set of results returned by Kinetica.aggregateKMeans(string,IList<string>,int,double,IDictionary<string, string>).
Definition at line 182 of file AggregateKMeans.cs.
Property Documentation
◆ count
|
getset |
The total count of all the clusters - will be the size of the input table.
Definition at line 198 of file AggregateKMeans.cs.
◆ counts
|
getset |
The number of elements in the cluster closest the corresponding k-means values.
Definition at line 190 of file AggregateKMeans.cs.
◆ means
|
getset |
The k-mean values found.
Definition at line 186 of file AggregateKMeans.cs.
◆ num_iters
|
getset |
The number of iterations the algorithm executed before it quit.
Definition at line 210 of file AggregateKMeans.cs.
◆ rms_dist
|
getset |
The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize.
Definition at line 202 of file AggregateKMeans.cs.
◆ rms_dists
|
getset |
The root mean squared distance of the elements in the cluster for each of the k-means values.
Definition at line 194 of file AggregateKMeans.cs.
◆ tolerance
|
getset |
The distance between the last two iterations of the algorithm before it quit.
Definition at line 206 of file AggregateKMeans.cs.
The documentation for this class was generated from the following file:
- Kinetica/Protocol/AggregateKMeans.cs
