Prediction: plugin a corelation table (neuron) into a Time-Series Neuron in Keras/ TF
i am adding more details
I have a time series of Babies (1,2,3) showing how many problem they have each week (Born week 1 to week 80) and in which organ (14 organ).
There is a separate numeric time-free correlation tables for babies/organs. showing Xtype blood cells per organ per baby -> Causes problems
My aim is to predict how many problem will NewBaby (Baby4) have, in which organ, per week
Predict this: Week1: 1 problem | Stomach Week1: 1 problem | Liver Week2: 1 problem | Stomach ..
TIME_SERIES_INPUT ------> LSTM (RNN?) -------\ -------------------------------------------------------------------> MERGE ---> AUXILIARY_INPUTS --> [do something] ----------/*
How can I model this problem with Keras/TF? To be specific firstly should I modify the dataset to include correlation tables. Or can I plug a model into LSTM? I have seen some examples on this board but they are mostly CNN that does not apply to my data set Ps I can insert whole dataset if needed
Thanks
DataSet Looks like
Week Baby Age Organ Date IssueFound Problem Type
2 Baby2 A0 Organ2 06/24/16 1 F
2 Baby3 A0 Organ11 05/01/17 1 F
2 Baby3 A0 Organ11 05/02/17 1 F
2 Baby3 A0 Organ13 05/03/17 1 F
2 Baby3 A0 Organ13 05/05/17 1 F
3 Baby2 A0 Organ12 06/29/16 1 F
3 Baby2 A0 Organ2 07/01/16 1 F
4 Baby3 A0 Organ13 05/18/17 1 F
4 Baby3 A0 Organ2 05/19/17 1 F
time-free Co relation Table looks like
New X-Type Blood Cell per Organ per baby
Organ Baby1 Baby2 Baby3 NewBaby
Bladder Organ1 288 247 97 253
Brain Organ2 2548 1972 992 251
Ears Organ3 32 254 162 155
Eyes Organ4 111 0 459 -89
Heart Organ5 42 1214 0 142
Kidney Organ6 4 188 186 -87
Kidneys Organ7 806 1764 796 153
Liver Organ8 658 657 -20 0
Lung Organ9 0 484 0 0
Nose Organ10 3328 9940 4435 3223
Pancreas Organ11 11 389 207 194
Skin Organ12 664 766 164 -145
Stomach Organ13 246 -71 0 -70
Tongue Organ14 1403 0 33 0
Topic keras time-series predictive-modeling machine-learning
Category Data Science