使用保存的模型进行机器学习,以使用weka(Eclipse+Java)进行预测
我对“Instances originalTrain=”这句话的论点感到困惑,因为我是新加入这个weka的人,谁能帮我纠正这个错误。我们正在使用java中的weka创建一个疾病预测系统
import weka.classifiers.Classifier;
import weka.core.Instances;
public class Main {
public static void main(String[] args) throws Exception
{
String rootPath="/some/where/";
Instances originalTrain= //instances here (don't know to complete this statement)
//load model
Classifier cls = (Classifier) weka.core.SerializationHelper.read(rootPath+"tree.model");
//predict instance class values
Instances originalTrain= //load or create Instances to predict (This statement too)
//which instance to predict class value
int s1=0;
//perform your prediction
double value=cls.classifyInstance(originalTrain.instance(s1));
//get the prediction percentage or distribution
double[] percentage=cls.distributionForInstance(originalTrain.instance(s1));
//get the name of the class value
String prediction=originalTrain.classAttribute().value((int)value);
System.out.println("The predicted value of instance "+
Integer.toString(s1)+
": "+prediction);
//Format the distribution
String distribution="";
for(int i=0; i <percentage.length; i=i+1)
{
if(i==value)
{
distribution=distribution+"*"+Double.toString(percentage[i])+",";
}
else
{
distribution=distribution+Double.toString(percentage[i])+",";
}
}
distribution=distribution.substring(0, distribution.length()-1);
System.out.println("Distribution:"+ distribution);
}
}
# 1 楼答案
为了完整起见,问题中的代码片段源自Get prediction percentage in WEKA using own Java code and a model
originalTrain应该是你的训练实例。我知道有两种方法可以向originalTrain添加实例
此方法从数据库加载数据。arff文件,并基于找到的指令here
您可以按照这个答案Define input data for clustering using WEKA API中的描述手动创建和添加实例