官术网_书友最值得收藏!

ELKI

ELKI creates an environment for developing KDD applications supported by index structures, with an emphasis on unsupervised learning. It provides various implementations for cluster analysis and outlier detection. It provides index structures such as R*-tree for performance boosting and scalability. It is widely used in research areas by students and faculties up until now and has been gaining attention from other parties recently.

ELKI uses the AGPLv3 license, and can be found at https://elki-project.github.io/. It is comprised of the following packages:

  • de.lmu.ifi.dbs.elki.algorithm: Contains various algorithms such as clustering, classification, itemset mining, and so on
  • de.lmu.ifi.dbs.elki.outlier: Defines an outlier-based algorithm
  • de.lmu.ifi.dbs.elki.statistics: Defines a statistical analysis algorithm
  • de.lmu.ifi.dbs.elki.database: This is the ELKI database layer
  • de.lmu.ifi.dbs.elki.index: This is for index structure implementation
  • de.lmu.ifi.dbs.elki.data: Defines various data types and database object types
主站蜘蛛池模板: 鲁甸县| 安阳市| 工布江达县| 广昌县| 莆田市| 鄂州市| 商南县| 达尔| 巨鹿县| 色达县| 都兰县| 安平县| 普兰店市| 诸城市| 农安县| 沭阳县| 宁化县| 晋宁县| 庄河市| 玉田县| 大宁县| 都昌县| 额济纳旗| 乐至县| 遂昌县| 志丹县| 资阳市| 枝江市| 永平县| 安顺市| 平和县| 万全县| 满洲里市| 南阳市| 马关县| 蚌埠市| 沈阳市| 香河县| 九寨沟县| 鄯善县| 肥西县|