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所在平台: Udemy |
课程主页: https://www.udemy.com/course/mastering-and-tuning-descision-trees/
课程评论：没有评论
**课程名称：** 精通与调优决策树 (Mastering and Tuning Decision Trees) **课程概览：** 本课程是关于IBM SPSS Modeler的系列自学视频，专注于讲解其内置的决策树方法（CHAID、C5.0、CRT和QUEST）。SPSS Modeler是一个数据挖掘工作台，无需编程即可快速直观地构建预测模型。分析师通常利用SPSS Modeler挖掘历史数据进行分析，并部署模型以对近期（甚至实时）数据进行预测。 这些决策树技术能够基于预测变量的值，为结果变量生成基于规则的预测模型。学生将学习： * 何时使用决策树技术 * 决策树方法的假设 * 如何自动执行分析以及如何进行交互式分析 * 如何解读分析结果 课程将特别详细地对比CHAID和C & RT方法。同时，课程还将演示如何通过调整参数来优化模型性能（即调优），并重点展示CHAID和C & RT的调优过程。
IBM SPSS Modeler is a data mining workbench that allows you to build predictive models quickly and intuitively without programming. Analysts typically use SPSS Modeler to analyze data by mining historical data and then deploying models to generate predictions for recent (or even real-time) data. Overview: Mastering and Tuning Decision Trees is a series of self-paced videos that discusses the decision tree methods (CHAID, C5.0, CRT, and QUEST) available in IBM SPSS Modeler. These techniques produces a rule based predictive model for an outcome variable based on the values of the predictor variables. Students will gain an understanding of the situations in which one would this technique, its assumptions, how to do the analysis automatically as well as interactively, and how to interpret the results. Particular emphasis is made on contrasting CHAID and C & RT in detail. Tuning - the adjusting of parameters to optimize performance - is demonstrated using both CHAID and C & RT.
