A set of results returned by Kinetica.aggregateKMeans. More…
Classes | |
| struct | Info |
| A set of string constants for the parameter AggregateKMeansResponse.info. More… | |
Properties | |
| IList< IList< double > > | means = new List<IList<double>>() [get, set] |
| The k-mean values found. | |
| IList< long > | counts = new List<long>() [get, set] |
| The number of elements in the cluster closest the corresponding k-means values. | |
| IList< double > | rms_dists = new List<double>() [get, set] |
| The root mean squared distance of the elements in the cluster for each of the k-means values. | |
| long | count [get, set] |
| The total count of all the clusters - will be the size of the input table. | |
| double | rms_dist [get, set] |
| The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize. | |
| double | tolerance [get, set] |
| The distance between the last two iterations of the algorithm before it quit. | |
| int | num_iters [get, set] |
| The number of iterations the algorithm executed before it quit. | |
| IDictionary< string, string > | info = new Dictionary<string, string>() [get, set] |
| Additional information. | |
| Properties inherited from kinetica.KineticaData | |
| Schema | Schema [get] |
| Avro Schema for this class. | |
Additional Inherited Members | |
| Public Member Functions inherited from kinetica.KineticaData | |
| KineticaData (KineticaType type) | |
| Constructor from Kinetica Type. | |
| KineticaData (System.Type type=null) | |
| Default constructor, with optional System.Type. | |
| object | Get (int fieldPos) |
| Retrieve a specific property from this object. | |
| void | Put (int fieldPos, object fieldValue) |
| Write a specific property to this object. | |
| KineticaData (KineticaType type) | |
| Constructor from Kinetica Type. | |
| KineticaData (System.Type type=null) | |
| Default constructor, with optional System.Type. | |
| object | Get (int fieldPos) |
| Retrieve a specific property from this object. | |
| void | Put (int fieldPos, object fieldValue) |
| Write a specific property to this object. | |
| 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. | |
| static ? RecordSchema | SchemaFromType (System.Type t, KineticaType? ktype=null) |
| Create an Avro Schema from a System.Type and a KineticaType. | |
Detailed Description
A set of results returned by Kinetica.aggregateKMeans.
Definition at line 421 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 446 of file AggregateKMeans.cs.
◆ counts
| getset |
The number of elements in the cluster closest the corresponding k-means values.
Definition at line 438 of file AggregateKMeans.cs.
◆ info
| getset |
Additional information.
- QUALIFIED_RESULT_TABLE_NAME: The fully qualified name of the result table (i.e. including the schema) used to store the results.
The default value is an empty Dictionary.
Definition at line 471 of file AggregateKMeans.cs.
◆ means
| getset |
The k-mean values found.
Definition at line 434 of file AggregateKMeans.cs.
◆ num_iters
| getset |
The number of iterations the algorithm executed before it quit.
Definition at line 458 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 450 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 442 of file AggregateKMeans.cs.
◆ tolerance
| getset |
The distance between the last two iterations of the algorithm before it quit.
Definition at line 454 of file AggregateKMeans.cs.
The documentation for this class was generated from the following files:
- _build/public-os_ubuntu24.04-arch_amd64-cc_gcc_13.3.0/install/Kinetica/Protocol/AggregateKMeans.cs
- Kinetica/Protocol/AggregateKMeans.cs