Masa Nakamura masayang

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Masayoshi Nakamura Consulting LLC
San Francisco, CA
01:24 (UTC -12:00)
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in/nakamuramasa

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masayang / 3x.py

Created October 9, 2012 04:42

Xが3次元

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

	X = np.array([[0, 0, 1], [1, 1, 2], [2, 2, 3], [3, 3, 3.1]])
	Y = np.array([0.1, 1.1, 1.8, 2.7])

	regr = linear_model.LinearRegression()
	regr.fit(X, Y)

masayang / readfromtxt.py

Created October 9, 2012 05:11

ファイルからの読み込み

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

	x = np.genfromtxt("source.csv", delimiter=",")

	plt.scatter(x[:,0], x[:,1])
	plt.savefig("readfromtxt.png")

masayang / bayes_simple.py

Created October 10, 2012 00:16

Naive Bayes (Simple)

	import numpy as np
	import matplotlib.pyplot as plt
	from sklearn.naive_bayes import GaussianNB

	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 / instruction.txt

Created October 10, 2012 00:44

Naive Bayes (Iris)

	http://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data

	上記にあるデータをiris.dataとして保存

masayang / Graphvizインストールと実行.txt

Created October 10, 2012 23:24

Decision Trees(Over fitting)

	$ sudo apt-get install graphviz
	$ dot -T png -o decisiontree_simple.png decisiontree_simple.graphviz

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])

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 / 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 / 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 / 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])