Supervised learning for time series data

Question

I have following time series data.I want to use classification model.for independent variable i want to pass an array of previous 5 values of feature 1 /feature 2 given some weight.for example on 06-03-2015 for id 1: [ a1 a2 a3 a4 a5] [0.053 0.036 0.044 0.087 0.02 ]

ID  feature1    Date    feature2    
1   0.053   02-03-2015  0.0115
1   0.05    08-03-2015  0.0117
1   0.099   09-03-2015  0.00355
1   0.006   10-03-2015  0.0088
1   0.007   11-03-2015  0.0968
1   0.0045  12-03-2015  0.08325
1   0.068   13-03-2015  0.0055
1   0.097   14-03-2015  0.0668
1   0.082   18-03-2015  0.0635
2   0.053   21-03-2015  0.0115
2   0.05    26-03-2015  0.0117
2   0.099   27-03-2015  0.00355
2   0.006   28-03-2015  0.0088
2   0.007   29-03-2015  0.0968
2   0.068   31-03-2015  0.0055
2   0.097   01-04-2015  0.0668
2   0.017   02-04-2015  0.0145
2   0.049   06-04-2015  0.0556

How would I assign weights to values on rolling basis where window =5 .weights can between 0 to 1 .so I can multiply them with values and result should go as 1 of the independent variable.How can i use LSTM model for this kind of data.

Answer 1

这篇关于 Machine Learning Mastery 的文章将带您了解如何做到这一点。