Time series forecasting with probability(python)

@pooja16 wrote:

We have time series data, where each data is segregated by # of days in a window.

In each window we have probability of event occurring. The event can be categorized as +ve or -ve but ultimately probability sums up to 1.

For ex.

The time series is divided by two week window

time        +ve event            -ve event

W1             0.7                   0.3

W2             0.4                   0.6

W3             0.2                   0.8

W4             ....                  ....

Now, we want to predict the probability of +ve event occurring/-ve event occurring in window 4

Couple questions:

1. How can we use Naive Bayes or other algorithms which use probability at it’s core?

2. Are there any other suitable Machine Learning Model for such class of problems?

3. I would appreciate, if I get sample code

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