Find the optimal changepoint value

[kevb10]

Documentation here

tldr; a higher value makes the model more flexible while a lower value makes it less flexible

This will have to be different for every stock.

delphi-oracle/stocker.py

Lines 338 to 359 in 5c95102

	def changepoint_prior_analysis(self, changepoint_priors=[0.001, 0.05, 0.1, 0.2], colors=['b', 'r', 'grey', 'gold']):
	# Training and plotting with specified years of data
	global predictions
	train = self.stock[
	(self.stock['Date'] > (max(self.stock['Date']) - pd.DateOffset(years=self.training_years)).date())]
	# Iterate through all the changepoints and make models
	for i, prior in enumerate(changepoint_priors):
	# Select the changepoint
	self.changepoint_prior_scale = prior
	# Create and train a model with the specified cps
	model = self.create_model()
	model.fit(train)
	future = model.make_future_dataframe(periods=180, freq='D')
	# Make a dataframe to hold predictions
	if i == 0:
	predictions = future.copy()
	future = model.predict(future)