Comments (5)
Hi @mustafakucuk0,
If you want to predict a Target column, you probably want to use it as output only. Thus you would only have a 4 dimensional input matrix with "Open, Close, High, Low".
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Hello again, I am everywhere hahaha. First of all, thank you for your kind answers. I appreciate that. My theoretical part in multivariate regression may not be enough, but I understand the main aim of the theory. In the above case, I want to predict target values using other features. So, using "Open,Close,High and Low" I want to forecast Target value of 1 step ahead. Is that logical? I'll try to elaborate on it with structured format. I am making the numbers up, so do not try to find a connection.
Open Close High Low Target
01 15 20 20 15 2
02 18 22 22 18 3
*
*
/ a b c d n
So, my data looks like this; is there possibility to forecast the target value of second row by using 4 features of first row ? When people try to work with multivariate time series, they include the Target value as a feature, but I think it would drive the model to overfitting, but I am not sure about it either. That is why I asked my question with including target value as a feature.
Thank your for time and this library again.
from reservoirpy.
Hello again,
Ok, now I understand better.
Yes you can try to predict the next step. In this case you should not include the target in your input, otherwise the model would probably do not learn the correct thing.
So you just need to do:
Open, Close, High, Low ---> reservoir ----> Open, Close, High, Low
Thus, the input and output dimensions are both 4, you predict the same variables you give in inputs.
Does it answer your questions?
from reservoirpy.
Hi again. I understand you suggestion but what about the time when we have Target value? Using these 4 features, I want to make the model predict the next Target value.
from reservoirpy.
For the time you just need to consider the next time step if you want to predict the next values,
or more generally the 'delta' time steps ahead:
[Open, Close, High, Low] (t) ---> reservoir ----> [Open, Close, High, Low](t + delta)
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Related Issues (20)
- Potential Error in Documentation HOT 1
- Segfault in classification notebook HOT 5
- Save/Load to/from disk HOT 2
- No warning is triggered when non-existing variable name is used
- Autograd - Feature Request HOT 1
- Mmap error with local parallelization with optuna from the tutorial HOT 1
- datasets.narma doesn't return input series HOT 5
- ValueError: Missing input data for node Reservoir-0.
- Fitting a model on non-temporal data HOT 1
- Feature Importance HOT 4
- Small-world reservoir matrices
- Rank list of degree of influence of input variables HOT 1
- I trying to forecast using reservoirpy HOT 1
- how to save and load a prediction model HOT 2
- Is the long term forecasting example opertion explanation correct HOT 3
- Understand and optimize ESN hyperparameters errors HOT 3
- cant do long term forecasting on yahoo stock market data HOT 4
- Creating a reservoir of custom nodes HOT 2
- LMS doesn't work for single node readout HOT 1
- ESN Parameter Effects HOT 7
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