- 数据挖掘过程和技术的基本知识
观众
- 数据分析师
- 数据科学家
Waikato Environment for Knowledge Analysis （Weka） 是一款开源数据挖掘可视化软体。它为数据准备、分类、聚类和其他数据挖掘活动提供了一组机器学习演算法。
此讲师指导的即时培训（在线或现场）面向希望使用 Weka 执行数据挖掘任务的初级到 中级数据分析师和数据科学家。
在本次培训结束时，参与者将能够：
- 安装并配置 Weka。
- 了解 Weka 环境和工作台。
- 使用 Weka 执行数据挖掘任务。
课程形式
- 互动讲座和讨论。
- 大量的练习和练习。
- 在即时实验室环境中动手实施。
课程自定义选项
- 要申请本课程的定制培训，请联系我们进行安排。
介绍
- 概览 Weka
- 了解数据挖掘过程
开始
- 安装与设定Weka
- 了解 Weka UI
- 设置环境和专案
- 探索 Weka 工作台
- 载入和浏览数据集
实施回归模型
- 了解不同的回归模型
- 处理和保存已处理的数据
- 使用交叉验证评估模型
- 序列化和可视化决策树模型
实现分类模型
- 了解特征选择和数据处理
- 构建和评估分类模型
- 构建和可视化决策树模型
- 以数位形式对文本数据进行编码
- 对文本数据执行分类
实现聚类分析模型
- 了解 K-means 聚类分析
- 规范化和可视化数据
- 执行 K-means 聚类分析
- 执行分层聚类
- 执行 EM 集群
部署 Weka 模型
故障排除
总结和后续步骤
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