Average Absolute Error

Refining exponential fit
f(t) = a*1/β e ^ t/β　+ C
β, a, c

Fit more generalized exponential

def fitFunc_gen(t, a, b, c):
	return a*(b)*numpy.exp(-b*t)+c

fitParams_gen, fitCov_gen = curve_fit(fitFunc_gen, division[0:len(division)])
fitParams_gen
fitCov_gen
(1/fitParams_gen[1])*fitParams_gen[0]+fitParams_gen[1]

Intertweet time:
t1, t2
<-Δt-><-p->

Training examples
(Δt, p)
elapsed time, time until next tweet

step_size = 10
data_points = []
for v in timeUntilNext:
	bin_left_edges = np.arange(0, v, step_size)

	for l_edge in bin_left_edges:
		tempNewPoint = [l_edge, v-1_edge]
		data_points.append(tempNewPoint)

data_points.sort()
delta 100 = [v[1] for v in data points if v[0]==100]

deltat_150 = [v[1] for v in data_points if v[0]==150]
deltat_10 = [v[1] for v in data_points if v[0]==10]

pandas.Series(deltat_10).hist(bins=30, alpha=0.5, color="blue")
d_150 = pandas.Series(deltat_150)
pandas.Series(deltat_150).hist(bins=30, alpha=0.3, color="red")