classification - How should I go about writing a naive Bayesian classifier in Python? -

I need to create a weather forecast system in Python. What happens to a file that contains weather data is ??? Such as temperature (average, maximum, minimum), air, dew point, moisture, position (fog, rain, snow, none) etc. And use it to train an intuitive Bayesian model so that it can predict the next day's situation, that is, the next day fog, rain, snow or any other.

This is part of an assignment, so the code provided that handles the input of the data file, I need to create a classifier, but I'm not sure how to do this.

Can anyone tell me in the right direction?

nltk.classify.nivebayes what modules are you looking for is. Here are examples in which there is an example. It shows how to classify the text, but some signals should be provided as to train the classifier based on the features of your weather.