Syncrossus

class Apprenant:
    """
    Classe modelisant un apprenant bayesien
    Attributs :
        classes : classes identifiees dans la base d'apprentissage
        valAttr : valeurs que peut prendre l'attribut des objets classables
        tableau : Chaque ligne est une classe, chaque colonne une valeur d'attribut.
                  Chaque cellule contient l'effectif de la base d'apprentissage correspondant.
                  ex :
                    |1.6|1.7|1.8|1.9

Syncrossus

% solution to the problem WWWDOT - GOOGLE = DOTCOM in prolog
carry(0).
carry(1).

digit(A) :- carry(A).
digit(2).
digit(3).
digit(4).
digit(5).
digit(6).

Syncrossus

Keybase proof

I hereby claim:

• I am syncrossus on github.
• I am syncrossus (https://keybase.io/syncrossus) on keybase.
• I have a public key ASDJ1fvJbb42jvF3Gn51iZ6dvz4d2IwfAfbQWb870hixSQo

To claim this, I am signing this object:

Syncrossus

# arguments :
#    labels1 : list of labels corresponding to the wrong clusters
#    labels2 : list of labels corresponding to the right clusters
# return :
#    labels1 relabeled
relabel <- function(labels1, labels2){
  newlabels <- labels1
  levels1 <- levels(as.factor(labels1))
  levels2 <- levels(as.factor(labels2))
  for(i in levels1){

Syncrossus

# Fisher's criterion computation function
# arguments :
#    clusters : list as returned by clustfisher (see below)
# return :
#    the value of the criterion
fisherCriterion <- function(clusters){
  diameterSum <- 0
  if(length(clusters$instants)==1){
    diameterSum <- sum(clusters$D[clusters$instants[1:length(clusters$instants)-1], clusters$instants[2:length(clusters$instants)]-1])
  }

Syncrossus

import numpy as np


def levenshtein(l1, l2):
    """ Computes Levenshtein distance between two list-like objects
        Args:
            l1, l2: subscriptable objects compatible with len()
                containing objects comparable with the `!=` operator.
    """
    # initializing the distance matrix

Syncrossus

import numpy as np


def score2rank(m):
    """ args:
            - m, a numpy matrix with 2 columns the 2nd of which should be numeric
        returns:
            - m with the second column's numbers switched for ranks
        example:
            m = [[a,5.8],    return = [[a,2],

Syncrossus

""" This module contains a simple identicon creation utility function.
    Original color palette : coolors.co/659bd8-ff776d-ffd793-9eefae-c99dba
"""
import hashlib
import random
import png  # requires pypng (version 0.0.19 recommended)
import sys

palette = {0: (255, 255, 255),
           1: (101, 155, 216),

Syncrossus

def dichotomy(ls, v, _i=0):
    """ Dichotomy search, or the optimal search for an item's index
        in a sorted list.
        Arguments:
            - (list) ls: the list in which to search, must be sorted for
                this to work
            - v: value to search for in the list, must be comparable to the
                items in the list
            - (int) _i: should not be used, is reserved for recursive purposes
        Returns:

Syncrossus

# Garbage matcher
# matches any string consisting of only |, <, >, +, *, ^, #, =, and hyphen chains.
# this is to identify patterns like ++<===> ######## <---->^^ which serve no purpose but to decorate the text
/(\||(--+)|(__+)|<|>|\+|\*|\^|#|=|~)+|(\\|_|\/){2,}/

# Garbage matcher 2
# matches anything that isn't a letter, space or basic punctuation.
# this is typically useful for cleaning up emojis
/.(?<!([a-zA-Z0-9]|,|\.|'| |\?|\!))/