masayang’s gists

masayang / djangoeb.js

Created November 3, 2012 01:04

CloudFormation script for Django/ElasticBeansTalk with Jenkins environment

	{
	"AWSTemplateFormatVersion" : "2010-09-09",

	"Description" : "AWS CloudFormation Template: This template installs a single-instance with dev environment for elastic beanstalk as well as Jenkins server. This template creates an Amazon EC2 instance. You will be billed for the AWS resources used if you create a stack from this template.",

	"Parameters" : {
	"EC2Tag" : {
	"Description" : "EC2 tag name",
	"Type" : "String"
	},

masayang / usarrests.csv

Created October 13, 2012 23:31

Ward Clustering

We can make this file beautiful and searchable if this error is corrected: It looks like row 2 should actually have 4 columns, instead of 5 in line 1.

	"Murder","Assault","UrbanPop","Rape"
	Alabama,13.2,236,58,21.2
	Alaska,10,263,48,44.5
	Arizona,8.1,294,80,31
	Arkansas,8.8,190,50,19.5
	California,9,276,91,40.6
	Colorado,7.9,204,78,38.7
	Connecticut,3.3,110,77,11.1
	Delaware,5.9,238,72,15.8
	Florida,15.4,335,80,31.9

masayang / km_unsupervised.py

Created October 13, 2012 03:18

K-Means Clustering(Unsupervised)

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn import cluster

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")
	x3 = np.genfromtxt("class3.csv", delimiter = ",")

	y1 = np.zeros(x1.shape[0])
	y2 = np.ones(x2.shape[0])

masayang / km_supervised.py

Created October 13, 2012 02:57

K-Means Clustering(Supervised)

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn import cluster

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")
	x3 = np.genfromtxt("class3.csv", delimiter = ",")

	y1 = np.zeros(x1.shape[0])
	y2 = np.ones(x2.shape[0])

masayang / kn_unsupervised.py

Created October 12, 2012 22:57

K-Neighbors Unsupervised

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn.neighbors import NearestNeighbors

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")
	x3 = np.genfromtxt("class3.csv", delimiter = ",")

	y1 = np.zerosimport numpy as np
	import matplotlib.pyplot as plt

masayang / kn_10.py

Created October 12, 2012 22:13

K-Neighbors Supervised

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn.neighbors import KNeighborsClassifier

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")
	x3 = np.genfromtxt("class3.csv", delimiter = ",")

	y1 = np.zeros(x1.shape[0])
	y2 = np.ones(x2.shape[0])

masayang / poly_svc.py

Created October 12, 2012 21:06

SVC kernels

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn import svm

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")
	x3 = np.genfromtxt("class3.csv", delimiter = ",")

	y1 = np.zeros(x1.shape[0])
	y2 = np.ones(x2.shape[0])

masayang / class3.csv

Created October 11, 2012 21:46

LinearSVM

	3.944800674823166098e+00	4.996271186415386367e+00
	5.547242838038199508e+00	5.414293869669647208e+00
	4.620646723315672943e+00	4.911930531086467155e+00
	4.846418245516238343e+00	3.584170537988319083e+00
	4.990222033288614689e+00	5.167624961159549279e+00
	5.832925679378353045e+00	6.730998187374821917e+00
	4.269651750644930743e+00	5.684499994023479275e+00
	6.382861274845375021e+00	5.195463145627869039e+00
	5.236782210357330491e+00	3.926700967069445269e+00
	4.672536804208451855e+00	4.868250521526301888e+00

masayang / randomforest_simple.py

Created October 11, 2012 01:33

Random Forest(max_depth = 3)

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn.ensemble import RandomForestClassifier

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")

	y1 = np.zeros(x1.shape[0])
	y2 = np.ones(x2.shape[0])

masayang / decisiontree_depth3.py

Created October 10, 2012 23:40

Decision Trees

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn import tree

	x1 = np.genfromtxt("class1.csv", delimiter = ",")
	x2 = np.genfromtxt("class2.csv", delimiter = ",")

	y1 = np.zeros(x1.shape[0])
	y2 = np.ones(x2.shape[0])

Masa Nakamura masayang