twolodzko

data {
  int<lower=3> n;
  vector[n] y;
  int<lower=0> h;
}
parameters {
  real<lower=0, upper=1> alpha;
  real<lower=0, upper=1> beta;
  real<lower=0> sigma;
  vector[2] mu_init;

twolodzko

library(ggplot2)
set.seed(123)

# simulated data
n <- 100
nx <- ny <- 500
x <- rbinom(n, nx, 0.22)
y <- rbinom(n, ny, 0.21)

twolodzko

twolodzko

twolodzko

from __future__ import print_function
import numpy as np


class RadialBasisFunctions(object):
    
    """Radial Basis Functions features for time-series data
    
    Parameters
    ----------

twolodzko

twolodzko

from collections import Counter

class PopularityEncoder(object):
    
    def __init__(self, vocab_size=50000):
        """Encode words according to popularity index
    
        Parameters
        ----------
   

twolodzko

twolodzko

# source: https://github.com/scikit-learn/scikit-learn/issues/10810#issuecomment-373164104

import copy

def prune(tree):
    tree = copy.deepcopy(tree)
    dat = tree.tree_
    nodes = range(0, dat.node_count)
    ls = dat.children_left
    rs = dat.children_right

twolodzko