Python createDataSet Examples

Example #1

File: main.py Project: hitdong/MachineLearningBook

def main():
    print 'Main Begin******************'

    group, labels = knn.createDataSet()

    print group, '\n', labels

    predict = [1, 0.9]
    label = knn.classify0(predict, group, labels, 3)

    print predict, ' lable is: ', label

    cp.predict()

    print 'Main End********************'

Example #2

File: test.py Project: DaPangYuanBuEr/datamining

# -*- coding: UTF-8 -*-    或者  #coding=utf-8
'''
Created on 2016年8月20日

@author: xiaoyuan
'''
import knn

group,labels = knn.createDataSet()
print knn.classify0([0,0], group, labels, 3)

Example #3

import knn
from numpy import *
#生成数据集和类别标签
dataSet,labels = knn.createDataSet()
#定义一个未知类别的数据
testX = array([5.9, 3.1, 5.1, 1.8])
k=3
#调用分类函数对未知数据分类
outputLabel = knn.kNNClassify(testX, dataSet, labels, 3)
print("Your input is:", testX, " and classified to class:", outputLabel)

Example #4

File: test_knn.py Project: Lou1sWang/MLCodeDive

import knn
group, labels = knn.createDataSet()
print(group, labels)
print(knn.classify0([0, 0], group, labels, 3))

Example #5

File: main.py Project: gatieme/AderXCoding

# coding=utf-8
import knn  
from numpy import *   
import matplotlib.pyplot as plt
import numpy as np

if __name__ == "__main__" :
    
    # create the dataset
    dataSet, labels = knn.createDataSet()  
    print dataSet
    # set the K value of KNN
    k = 3  
    # classify using kNN 
    ## test1 data(1.2, 1.0)
    testX = array([1.2, 1.0])   

    outputLabel = knn.kNNClassify(testX, dataSet, labels, k)  
    print "Your input is:", testX, "and classified to class: ", outputLabel  
    ## test1  data(0.1, 0.3)
    testX = array([0.1, 0.3])  
    outputLabel = knn.kNNClassify(testX, dataSet, labels, k)  
    print "Your input is:", testX, "and classified to class: ", outputLabel