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weka-3-4-12
- weka全名是怀卡托智能分析环境（Waikato Environment for Knowledge Analysis），是一个公开的数据挖掘工作平台，集合了大量能承担数据挖掘任务的机器学习算法，包括对数据进行预处理，分类，回归、聚类、关联规则以及在新的交互式界面上的可视化-full name is weka intelligent analysis environment Waikato (Waikato Environment fo
weka-src
- weka 3.7源代码包 WEKA的全名是怀卡托智能分析环境(Waikato Environment for Knowledge Analysis)-weka 3.7 source code package WEKA full name is the intelligent analysis of the environment Waikato (Waikato Environment for Knowledge Analys
jBNC
- jBNC is a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data m
associations
- public class DiscreteEstimator extends java.lang.Object implements Estimator Simple symbolic probability estimator based on symbol counts. Version: $Revision: 1.6 $ Author: Len Trigg (trigg@cs.waika
WEKA-EDU
- Weka的全名是怀卡托智能分析环境（Waikato Environment for Knowledge Analysis），是一款免费的，非商业化（与之对应的是SPSS公司商业数据挖掘产品--Clementine ）的，基于JAVA环境下开源的机器学习（machine learning）以及数据挖掘（data minining）软件。它和它的源代码可在其官方网站下载。有趣的是，该软件的缩写WEKA也是New Zealand独有的一种鸟名
weka-3-7-7
- Weka的全名是怀卡托智能分析环境（Waikato Environment for Knowledge Analysis），是一款免费的，非商业化（与之对应的是SPSS公司商业数据挖掘产品--Clementine ）的，基于JAVA环境下开源的机器学习（machine learning）以及数据挖掘（data minining）软件。这是2012年8月下旬的最新版本。-The full name of the Weka Waikato
Naivebayes-classification
- 简单朴素贝叶斯 分类器，针对数值型和名称型属性的分类基本算法。-Simple bayesian classifier, in view of the numeric type and name attributes the classification of the basic algorithm.NaiveBayesSimple.java * Copyright (C) 1999 University of Waikato,
impoetant
- Correlation-based Feature Selection for Machine Learning for the degree of Doctor of Philosophy at The University of Waikato
weka-new
- Weka的全名是怀卡托智能分析环境(Waikato Environment for Knowledge Analysis)，是一款免费的，非商业化(与之对应的是SPSS公司商业数据挖掘产品--Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to
Waikato Driveaways
- driveways apps to display cars in list
moa-release-2016.04
- MOA Machine Learning for Streams。它包括一系列机器学习算法（分类，回归，聚类，异常值检测，概念漂移检测和推荐系统）以及评估工具。与WEKA项目相关的MOA也是用Java编写的，同时扩展到更严苛的问题。 https://moa.cms.waikato.ac.nz/(It includes a series of machine learning algorithms (classification, re