Robert Griesmeyer griesmey

🏠

Working from home

griesmey / mapping.sc

Created October 12, 2016 16:09

	def squareList(xs: List[Int]): List[Int] = xs match {
	case Nil => xs
	case y :: ys => y * y :: squareList(ys)
	}

	def squareList1(xs: List[Int]): List[Int] =
	xs map (y => y * y)

griesmey / mergesort.sc

Created October 12, 2016 15:59

Mergesort with Implicit Type ordering

	import math.Ordering

	def msort[T](xs: List[T])(implicit ord: Ordering[T]): List[T] = {
	val n = xs.length / 2
	if (n == 0) xs
	else {
	def merge(xs: List[T], ys: List[T]): List[T] =
	(xs, ys) match {
	case (Nil, ys) => ys
	case (xs, Nil) => xs

griesmey / gist:163d749f7a5fca65f5d9

Created October 15, 2015 22:34

Algorithm to check if a tree is a binary search tree

griesmey / bigram_gist.py

Created September 21, 2015 04:35

quick bigram gist; You can use the dictVectorizer and the Tfidf transformer to generate your features

	from collections import Counter
	import re
	from sklearn.feature_extraction import DictVectorizer
	from sklearn.feature_extraction.text import TfidfTransformer
	from sklearn.feature_extraction.text import CountVectorizer
	from itertools import islice, tee
	from nltk.corpus import stopwords

	def tokenize(sentence):
	words = re.findall("[a-zA-Z]+", sentence)

griesmey / .ipynb

Created September 21, 2015 04:33

Bigrams stuff

	from itertools import islice, tee
	from nltk.corpus import stopwords

griesmey / kmeans.py

Created August 18, 2015 16:31

implementation of KMeans in Python

	from math import sqrt
	import sys
	from collections import defaultdict
	from itertools import izip


	class Point(object):
	def __init__(self, x, y, id=None):
	self.x = x
	self.y = y

griesmey / TestKNN.py

Created January 27, 2012 01:46

Python script to automate tests for K-nearest Neighbor algorithm

	import glob
	import get_data
	import run_knn
	from math import *


	__author__ = 'Robert Griesmeyer'
	__date__ = 'May 21st 2011'
	__doc__ = """ This module is for the use of accuaracy checking of the\
	k-nearest neighbor algorithm execution. The parts tested are the predictions\