What are the attributes used in time series to be forecasted using SVM? I have two values the date and the value at that date for the class I already know that I can use -1 and 1 when price gets up or down but still don't know how to plot the time series to calculate the hyperplane
time series forecasting using Support Vector Machine
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There are some papers that show some ways to do it:
Financial time series forecasting using support vector machine
Using Support Vector Machines in Financial Time Series Forecasting
Financial Forecasting Using Support Vector Machines
I really recommend that you go through the existent literature, but just for fun I will describe an easy way (probably not the best) to do it.
Let's say you have N pairs where is the particular date/time of the pair and its corresponding value. The pairs are sorted by its X component.
Let's say you want to predict if given , the corresponding unknown value will go up or down (Notice that you could also use regression and instead try to predict the value itself).
Then we could train a model with a training set like this:
Basically, you will be training the algorithm to make an educated guess of the next "tick" in the future by given to it a glimpse of the past. Once your model is trained to make a prediction you feed the model with the N values (where N is the amount of values you used as input in your training phase) previous to the value you want to predict.