api:dk11:activex:tatukgis_xdk11.tgis_classificationmethod

DK11 for ActiveX
| TatukGIS_XDK11.**TGIS_ClassificationMethod**
| Enums

Enumeration of classification methods.

// C# public enum TGIS_ClassificationMethod { DefinedInterval = 0, EqualInterval = 1, GeometricalInterval = 2, KMeans = 3, KMeansSpatial = 4, NaturalBreaks = 5, Quantile = 6, Quartile = 7, StandardDeviation = 8, StandardDeviationWithCentral = 9, Unique = 10, Manual = 11 }

' VisualBasic Public Enum TGIS_ClassificationMethod DefinedInterval = 0 EqualInterval = 1 GeometricalInterval = 2 KMeans = 3 KMeansSpatial = 4 NaturalBreaks = 5 Quantile = 6 Quartile = 7 StandardDeviation = 8 StandardDeviationWithCentral = 9 Unique = 10 Manual = 11 End Enum

// Oxygene type TGIS_ClassificationMethod = public ( DefinedInterval = 0, EqualInterval = 1, GeometricalInterval = 2, KMeans = 3, KMeansSpatial = 4, NaturalBreaks = 5, Quantile = 6, Quartile = 7, StandardDeviation = 8, StandardDeviationWithCentral = 9, Unique = 10, Manual = 11 );

Name | Value | Description | |
---|---|---|---|

DefinedInterval | 0 | The interval between class breaks is defined by the user through the Interval property. Number of classes is determined automatically and can be gotten from the NumClasses property. | |

EqualInterval | 1 | The range of attribute values is partitioned into equal-sized subranges by defining the number of classes through the NumClasses property. | |

GeometricalInterval | 2 | Class breaks are based on class intervals that have a geometrical series. User specifies the number of class intervals through the NumClasses property. | |

KMeans | 3 | Class breaks are determined using the K-Means Clustering Algorithm. All values from an attribute are divided into N=NumClasses clusters so the within-cluster sum of squares is minimized. | |

KMeansSpatial | 4 | K-Means algorithm is used to partition data into N=NumClasses spatial clusters based on objects centroids. Available only for vector layers. New field named 'KMEANS_ID' will be added or updated if it exists. | |

NaturalBreaks | 5 | Class breaks are determined using the Fisher's Exact Optimization algorithm. Dataset is divided into N=NumClasses clusters so that the between-cluster sum of squares is maximized. This is default method. | |

Quantile | 6 | Class intervals are created to have an equal number of observations. Number of classes can be defined through the NumClasses property. This method is also known as Equal Count. | |

Quartile | 7 | Quantile method is applied with fixed property NumClasses=4. This method creates class breaks at the first, second, and third quartiles i.e. at 25-th, 50-th, and 75-th percentiles respectively. | |

StandardDeviation | 8 | Class breaks are set above and below the mean of the attribute values at intervals, for example at 1, 1/2, 1/3, or 1/4 standard deviations until all the data values are contained within these ranges. Interval is specified through the Interval property. This method produces even number of classes. | |

StandardDeviationWithCentral | 9 | Same as StandardDeviation but class breaks are shifted by a half of the interval to get central class in range [Mean-Interval/2..Mean+Interval/2]. For example, if Interval equals 1 Std Dev, central class is limited by breaks -0.5 Std Dev and 0.5 Std Dev. This method produces odd number of classes. | |

Unique | 10 | Class breaks are set for unique values. Number of classes can be limited through the NumClasses property. | |

Manual | 11 | Class breaks are set manually by the user through the AddClassBreak method. This method is used when classes are meaningful. | |

**K-Means Spatial**

By default, `KMeansSpatial`

classification method works with 2-dimensional data - using objects' centroids (X, Y).

To perform an algorithm in 3D, set `Field`

property with Z-data. You can use one of the built-in fields, such as `GIS_COORD_Z`

, `GIS_CENTER_Z`

, or any numerical existing field.

2022/11/16 01:08