SYMBOL INDEX (171 symbols across 26 files)

FILE: AdaBoost/ROC.py
  function loadDataSet (line 17) | def loadDataSet(fileName):
  function stumpClassify (line 31) | def stumpClassify(dataMatrix,dimen,threshVal,threshIneq):
  function buildStump (line 50) | def buildStump(dataArr,classLabels,D):
  function adaBoostTrainDS (line 85) | def adaBoostTrainDS(dataArr, classLabels, numIt = 40):
  function plotROC (line 120) | def plotROC(predStrengths, classLabels):

FILE: AdaBoost/adaboost.py
  function loadSimpData (line 16) | def loadSimpData():
  function showDataSet (line 33) | def showDataSet(dataMat, labelMat):
  function stumpClassify (line 55) | def stumpClassify(dataMatrix,dimen,threshVal,threshIneq):
  function buildStump (line 74) | def buildStump(dataArr,classLabels,D):
  function adaBoostTrainDS (line 109) | def adaBoostTrainDS(dataArr, classLabels, numIt = 40):
  function adaClassify (line 144) | def adaClassify(datToClass,classifierArr):

FILE: AdaBoost/horse_adaboost.py
  function loadDataSet (line 16) | def loadDataSet(fileName):
  function stumpClassify (line 30) | def stumpClassify(dataMatrix,dimen,threshVal,threshIneq):
  function buildStump (line 49) | def buildStump(dataArr,classLabels,D):
  function adaBoostTrainDS (line 84) | def adaBoostTrainDS(dataArr, classLabels, numIt = 40):
  function adaClassify (line 118) | def adaClassify(datToClass,classifierArr):

FILE: AdaBoost/sklearn_adaboost.py
  function loadDataSet (line 17) | def loadDataSet(fileName):

FILE: Decision Tree/Decision Tree.py
  function calcShannonEnt (line 22) | def calcShannonEnt(dataSet):
  function createDataSet (line 51) | def createDataSet():
  function splitDataSet (line 86) | def splitDataSet(dataSet, axis, value):
  function chooseBestFeatureToSplit (line 109) | def chooseBestFeatureToSplit(dataSet):
  function majorityCnt (line 145) | def majorityCnt(classList):
  function createTree (line 169) | def createTree(dataSet, labels, featLabels):
  function getNumLeafs (line 202) | def getNumLeafs(myTree):
  function getTreeDepth (line 226) | def getTreeDepth(myTree):
  function plotNode (line 254) | def plotNode(nodeTxt, centerPt, parentPt, nodeType):
  function plotMidText (line 276) | def plotMidText(cntrPt, parentPt, txtString):
  function plotTree (line 297) | def plotTree(myTree, parentPt, nodeTxt):
  function createPlot (line 331) | def createPlot(inTree):
  function classify (line 358) | def classify(inputTree, featLabels, testVec):
  function storeTree (line 384) | def storeTree(inputTree, filename):
  function grabTree (line 402) | def grabTree(filename):

FILE: Logistic/LogRegres-gj.py
  function loadDataSet (line 25) | def loadDataSet():
  function sigmoid (line 52) | def sigmoid(inX):
  function gradAscent (line 73) | def gradAscent(dataMatIn, classLabels):
  function stocGradAscent1 (line 108) | def stocGradAscent1(dataMatrix, classLabels, numIter=150):
  function plotBestFit (line 141) | def plotBestFit(weights):
  function plotWeights (line 180) | def plotWeights(weights_array1,weights_array2):

FILE: Logistic/LogRegres.py
  function Gradient_Ascent_test (line 23) | def Gradient_Ascent_test():
  function loadDataSet (line 52) | def loadDataSet():
  function sigmoid (line 79) | def sigmoid(inX):
  function gradAscent (line 99) | def gradAscent(dataMatIn, classLabels):
  function plotDataSet (line 128) | def plotDataSet():
  function plotBestFit (line 163) | def plotBestFit(weights):

FILE: Logistic/colicLogRegres.py
  function sigmoid (line 22) | def sigmoid(inX):
  function stocGradAscent1 (line 43) | def stocGradAscent1(dataMatrix, classLabels, numIter=150):
  function gradAscent (line 75) | def gradAscent(dataMatIn, classLabels):
  function colicTest (line 106) | def colicTest():
  function classifyVector (line 147) | def classifyVector(inX, weights):
  function colicSklearn (line 168) | def colicSklearn():

FILE: Naive Bayes/bayes-modify.py
  function createVocabList (line 21) | def createVocabList(dataSet):
  function setOfWords2Vec (line 42) | def setOfWords2Vec(vocabList, inputSet):
  function bagOfWords2VecMN (line 66) | def bagOfWords2VecMN(vocabList, inputSet):
  function trainNB0 (line 90) | def trainNB0(trainMatrix,trainCategory):
  function classifyNB (line 125) | def classifyNB(vec2Classify, p0Vec, p1Vec, pClass1):
  function textParse (line 147) | def textParse(bigString):                                               ...
  function spamTest (line 166) | def spamTest():

FILE: Naive Bayes/bayes.py
  function loadDataSet (line 20) | def loadDataSet():
  function createVocabList (line 44) | def createVocabList(dataSet):
  function setOfWords2Vec (line 65) | def setOfWords2Vec(vocabList, inputSet):
  function trainNB0 (line 91) | def trainNB0(trainMatrix,trainCategory):
  function classifyNB (line 126) | def classifyNB(vec2Classify, p0Vec, p1Vec, pClass1):
  function testingNB (line 150) | def testingNB():

FILE: Naive Bayes/nbc.py
  function TextProcessing (line 27) | def TextProcessing(folder_path, test_size = 0.2):
  function MakeWordsSet (line 88) | def MakeWordsSet(words_file):
  function TextFeatures (line 114) | def TextFeatures(train_data_list, test_data_list, feature_words):
  function words_dict (line 140) | def words_dict(all_words_list, deleteN, stopwords_set = set()):
  function TextClassifier (line 169) | def TextClassifier(train_feature_list, test_feature_list, train_class_li...

FILE: Regression Trees/regTrees.py
  function loadDataSet (line 5) | def loadDataSet(fileName):
  function plotDataSet (line 25) | def plotDataSet(filename):
  function binSplitDataSet (line 49) | def binSplitDataSet(dataSet, feature, value):
  function regLeaf (line 68) | def regLeaf(dataSet):
  function regErr (line 82) | def regErr(dataSet):
  function chooseBestSplit (line 96) | def chooseBestSplit(dataSet, leafType = regLeaf, errType = regErr, ops =...
  function createTree (line 150) | def createTree(dataSet, leafType = regLeaf, errType = regErr, ops = (1, ...
  function isTree (line 180) | def isTree(obj):
  function getMean (line 195) | def getMean(tree):
  function prune (line 211) | def prune(tree, testData):

FILE: Regression/abalone.py
  function loadDataSet (line 6) | def loadDataSet(fileName):
  function lwlr (line 31) | def lwlr(testPoint, xArr, yArr, k = 1.0):
  function lwlrTest (line 59) | def lwlrTest(testArr, xArr, yArr, k=1.0):
  function standRegres (line 80) | def standRegres(xArr,yArr):
  function rssError (line 101) | def rssError(yArr, yHatArr):

FILE: Regression/lego.py
  function scrapePage (line 6) | def scrapePage(retX, retY, inFile, yr, numPce, origPrc):
  function ridgeRegres (line 64) | def ridgeRegres(xMat, yMat, lam = 0.2):
  function setDataCollect (line 86) | def setDataCollect(retX, retY):
  function regularize (line 105) | def regularize(xMat, yMat):
  function rssError (line 131) | def rssError(yArr,yHatArr):
  function standRegres (line 146) | def standRegres(xArr,yArr):
  function crossValidation (line 167) | def crossValidation(xArr, yArr, numVal = 10):
  function ridgeTest (line 212) | def ridgeTest(xArr, yArr):
  function useStandRegres (line 239) | def useStandRegres():
  function usesklearn (line 260) | def usesklearn():

FILE: Regression/regression.py
  function loadDataSet (line 6) | def loadDataSet(fileName):
  function ridgeRegres (line 31) | def ridgeRegres(xMat, yMat, lam = 0.2):
  function ridgeTest (line 53) | def ridgeTest(xArr, yArr):
  function plotwMat (line 80) | def plotwMat():
  function regularize (line 103) | def regularize(xMat, yMat):
  function rssError (line 126) | def rssError(yArr,yHatArr):
  function stageWise (line 141) | def stageWise(xArr, yArr, eps = 0.01, numIt = 100):
  function plotstageWiseMat (line 179) | def plotstageWiseMat():

FILE: Regression/regression_old.py
  function loadDataSet (line 6) | def loadDataSet(fileName):
  function standRegres (line 31) | def standRegres(xArr,yArr):
  function plotDataSet (line 53) | def plotDataSet():
  function plotRegression (line 77) | def plotRegression():
  function plotlwlrRegression (line 104) | def plotlwlrRegression():
  function lwlr (line 146) | def lwlr(testPoint, xArr, yArr, k = 1.0):
  function lwlrTest (line 174) | def lwlrTest(testArr, xArr, yArr, k=1.0):

FILE: SVM/svm-digits.py
  class optStruct (line 17) | class optStruct:
    method __init__ (line 27) | def __init__(self, dataMatIn, classLabels, C, toler, kTup):
  function kernelTrans (line 40) | def kernelTrans(X, A, kTup):
  function loadDataSet (line 61) | def loadDataSet(fileName):
  function calcEk (line 78) | def calcEk(oS, k):
  function selectJrand (line 91) | def selectJrand(i, m):
  function selectJ (line 106) | def selectJ(i, oS, Ei):
  function updateEk (line 133) | def updateEk(oS, k):
  function clipAlpha (line 146) | def clipAlpha(aj,H,L):
  function innerL (line 162) | def innerL(i, oS):
  function smoP (line 219) | def smoP(dataMatIn, classLabels, C, toler, maxIter, kTup = ('lin',0)):
  function img2vector (line 257) | def img2vector(filename):
  function loadImages (line 273) | def loadImages(dirName):
  function testDigits (line 296) | def testDigits(kTup=('rbf', 10)):

FILE: SVM/svm-simple.py
  function loadDataSet (line 23) | def loadDataSet(fileName):
  function selectJrand (line 50) | def selectJrand(i, m):
  function clipAlpha (line 74) | def clipAlpha(aj,H,L):
  function showDataSet (line 98) | def showDataSet(dataMat, labelMat):
  function smoSimple (line 133) | def smoSimple(dataMatIn, classLabels, C, toler, maxIter):
  function showClassifer (line 211) | def showClassifer(dataMat, w, b):
  function get_w (line 259) | def get_w(dataMat, labelMat, alphas):

FILE: SVM/svm-smo.py
  class optStruct (line 17) | class optStruct:
    method __init__ (line 26) | def __init__(self, dataMatIn, classLabels, C, toler):
  function loadDataSet (line 36) | def loadDataSet(fileName):
  function calcEk (line 53) | def calcEk(oS, k):
  function selectJrand (line 66) | def selectJrand(i, m):
  function selectJ (line 81) | def selectJ(i, oS, Ei):
  function updateEk (line 108) | def updateEk(oS, k):
  function clipAlpha (line 121) | def clipAlpha(aj,H,L):
  function innerL (line 137) | def innerL(i, oS):
  function smoP (line 194) | def smoP(dataMatIn, classLabels, C, toler, maxIter):
  function showClassifer (line 231) | def showClassifer(dataMat, classLabels, w, b):
  function calcWs (line 270) | def calcWs(alphas,dataArr,classLabels):

FILE: SVM/svm-svc.py
  function img2vector (line 18) | def img2vector(filename):
  function handwritingClassTest (line 40) | def handwritingClassTest():

FILE: SVM/svmMLiA.py
  class optStruct (line 17) | class optStruct:
    method __init__ (line 27) | def __init__(self, dataMatIn, classLabels, C, toler, kTup):
  function kernelTrans (line 40) | def kernelTrans(X, A, kTup):
  function loadDataSet (line 61) | def loadDataSet(fileName):
  function calcEk (line 78) | def calcEk(oS, k):
  function selectJrand (line 91) | def selectJrand(i, m):
  function selectJ (line 106) | def selectJ(i, oS, Ei):
  function updateEk (line 133) | def updateEk(oS, k):
  function clipAlpha (line 146) | def clipAlpha(aj,H,L):
  function innerL (line 162) | def innerL(i, oS):
  function smoP (line 219) | def smoP(dataMatIn, classLabels, C, toler, maxIter, kTup = ('lin',0)):
  function testRbf (line 257) | def testRbf(k1 = 1.3):
  function showDataSet (line 290) | def showDataSet(dataMat, labelMat):

FILE: kNN/1.简单k-NN/kNN_test01.py
  function createDataSet (line 17) | def createDataSet():
  function classify0 (line 42) | def classify0(inx, dataset, labels, k):

FILE: kNN/1.简单k-NN/kNN_test01_old_method.py
  function createDataSet (line 16) | def createDataSet():
  function classify0 (line 37) | def classify0(inX, dataSet, labels, k):

FILE: kNN/2.海伦约会/kNN_test02.py
  function classify0 (line 24) | def classify0(inX, dataSet, labels, k):
  function file2matrix (line 67) | def file2matrix(filename):
  function showdatas (line 113) | def showdatas(datingDataMat, datingLabels):
  function autoNorm (line 186) | def autoNorm(dataSet):
  function datingClassTest (line 216) | def datingClassTest():
  function classifyPerson (line 252) | def classifyPerson():

FILE: kNN/3.数字识别/kNN_test03.py
  function classify0 (line 20) | def classify0(inX, dataSet, labels, k):
  function img2vector (line 60) | def img2vector(filename):
  function handwritingClassTest (line 86) | def handwritingClassTest():

FILE: kNN/3.数字识别/kNN_test04.py
  function img2vector (line 18) | def img2vector(filename):
  function handwritingClassTest (line 44) | def handwritingClassTest():