搜索资源列表
Machine_learning
- Machine Learning with WEKA: An Introduction （讲义） 关于数据挖掘和机器学习的.-Machine Learning with WEKA : An Introduction (s) on the Data Mining and Machine Learning.
Weka-3-2
- Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classi
Machine_learning
- Machine Learning with WEKA: An Introduction （讲义） 关于数据挖掘和机器学习的.-Machine Learning with WEKA : An Introduction (s) on the Data Mining and Machine Learning.
Weka-3-2
- Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classi
weka-src
- Weka，一个数据挖掘工具。功能包括：分类、聚类和关联规则等等。这是该开源软件的源代码，版本为3.5.7-Weka, a data mining tool. Features include: classification, clustering and association rules, etc.. This is the open source software source code, version 3.5.7
call_weka_in_matlab
- This example demonstrates how to use WEKA s SVMs classifier in Matlab.
MakeDensityBasedClusterer.java.tar
- 基于局部搜索能力强、收敛速度快的特点,首先初始化一个没有子种群的全局种群,再在全局种群中采用迭代搜索,并对其中的个体进行聚类,当聚类簇中的个体数目达到规定的最小规模时形成一个子种群,然后在各子种群中进行迭代搜索并重新进行聚类,从而提高进化过程中种群的多样性,增强算法跳出局部最优的能力.该算法基于weka，用于weka拓展功能，需要 weka算法包支持。-Based on the local search ability, the cha
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
Modeling-in-Starcraft-II
- 一篇人工智能领域的论文，作者利用weka环境选择合适的分类器对星际争霸2的录像数据进行玩家行为建模，旨在提高AI对玩家水平的判断。文章难度不高，对于初学人工智能和模式识别的很有启发性。-An artificial intelligence paper, the authors use weka environment select the appropriate classification for StarCraft 2‘s vide
fs_sup_fcbf
- Using Weka s feature selection algorithm X, the features on current trunk, each colum is a feature vector on all instances, and each row is a part of the instance Y, the label of instances, in single column for