在此示例中，如何使用基于规则的学习算法 [英] How can I use the rule-based learning algorithms for this example

问题描述

我具有以下数据，以便进行预测性学习，以了解人们在网上购买服装时在模型中发现什么功能很有吸引力.

I have data as follows in order to do a predictive learning as to what feature do people find attractive in a model when purchasing clothes online.

所以我的数据如下.

COLORofCLOTHING  MODELHAIR_COLOR MODEL_BUILD SELLER_CATEGORY
  Red               Black         Lean           1
  Blue              Brown         Lean           5
  Black             Blonde        Healthy        10

根据一组属性，为了预测服装是否卖得好. 但是，卖方类别可以介于1到10之间(1表示最佳，10表示最差).我不确定如何解决此问题.我正在为此目的使用weka.人们能否给我关于如何解决这个问题的想法?

In order to predict if the clothing will sell well given a set of attributes. However seller category can be anything between 1 to 10 (1 being best and 10 being worst) I am not sure how to approach this problem. I am using weka for this purpose. Can people please give me ideas on how to approach this problem?

基本上，我想建立一个模型来学习衣服的颜色等特征，并可以预测衣服的销售情况.

basically I want to build a model which learns the features like color of the clothing etc and can predict how well the clothes will sell.

推荐答案

将数据集转换并归一化为类似于以下内容的内容:

Transform and normalise your dataset into something along the lines of:

 color_red   color_blue color_black  hair_black  hair_brown  hair_blonde ... prediction
 1           0          0            1           0           0           ... 0
 0           1          0            0           1           0           ... 0.5
 0           0          1            0           0           1           ... 1

随机森林和神经网络应该能够为您提供预测.

Random Forests and Neural Networks should be able to give you predictions.

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