adamwlev

## Define a class for a Natural Spline
## https://web.stanford.edu/~hastie/Papers/ESLII.pdf#page=163
class NaturalSpline():
    def __init__(self,n_folds=6):
        self.n_folds = n_folds
        
    def get_mat(self,x,df):
        notches = np.percentile(x,np.linspace(0,100,df+2)[1:-1])
        X = np.column_stack(([1.0]*len(x),x))
        def d(x,e_k,e_K):

adamwlev

import numpy as np

def produce_transformation(tuples,tuples_t):
	"""
	Given points in some 2d space, and points in a transformed
	2d space, produces function to tranform one space to other.

	tuples : points in original space (list of x,y tuples)
	tuples_t : corresponding points in transformed space (")
	"""

adamwlev

license: gpl-3.0

adamwlev

## Makes a monitor where the mean of last x oob improvements
## are used to determine early stopping. This can be ammended
## to any stopping criteria one sees as fit - consecutive x 
## negatives, more negatives than positives in last x, etc.
def make_monitor(running_mean_len):
    def monitor(i,self,args):
        if np.mean(self.oob_improvement_[max(0,i-running_mean_len+1):i+1])<0:
            return True
        else:

adamwlev