Encog Neural Network错误正在减少，但在训练，验证，测试集中输出不正确

4 7,0664 0,620629058018605 输出标准化范围是-19到23.即使我评估训练集也没关系或测试集的结果如上。似乎网络只是在一些范围之间映射理想输出，在这种情况下从0.4-0.6。应该感谢有关此的任何信息。 我附上学习过程图和结果，还有。 除了标准化还有任何数据预处理阶段吗？ 图片： （找不到任何附件标签，抱歉给出链接） 学习图是否可以，始终在开头的交叉验证低于学习错误？ 评估图蓝色条是网络的外部（非规范化），红色条是理想值。如果你像我说的那样注意蓝色条（实际输出）在一定范围内，而理想值是多样的。 我希望我已经清楚地描述了我的问题并希望有人遇到这样的问题。Learning algorithm is ResilientPropagation,so i have dataset of 6.000 records and the network is learning so fast like in 5-6 iterations the error rate becomes around 7-8 percent and one of the strange things is that when i evaluate the network i get an output between 0.4-0.62 even if i pass the training set, futhermore all of the data (training,validation,test sets) are normalized from 0 to 1. And another issue is that the outputs produced by the network are completely wrong, for instanceReality Normalized OutputUnnormalized Output2-0,98 0,429047583164628-15-0,9272 0,430304819968970-0,8159 0,432954942682462-6-0,8001 0,43333207603265614-0,7878 0,433624916240407-6-0,6205 0,43760826315651386,3781 0,60424151755008186,5203 0,6076268200195776,5353 0,607983605999036-156,6413 0,61050762727015447,0664 0,620629058018605Output normalization range is from -19 to 23. It doesn't matter even if i evaluate the training set or test set the results are like above. The seems like the network is just mapping the ideal outputs between some range,in this case from 0.4-0.6.Would appreciate any info concerning this.I am attaching the learning process graph and the results, a diagramm also.Besides normalization are there any data preproccesing stages?The images:(couldn't find any attachment tags, sorry giving the links)The learning graph Is it okay, that the cross validation always in the beginning is below the learning error?Evaluation Diagram the blue bar is the outpur of the network(denormalized) and the red one is the ideal value. If you pay attention like i said the blue bar(actual output) sticks to some range whereas the ideal values are diverse.I hope i've described my problem clearly and hope that someone has encountered such a problem.推荐答案 这篇关于Encog Neural Network错误正在减少，但在训练，验证，测试集中输出不正确的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！