SYMBOL INDEX (30 symbols across 9 files)

FILE: Adaboost/adaboost.py
  function loadSimpData (line 9) | def loadSimpData():
  function stumpClassify (line 20) | def stumpClassify(dataMatrix,dimen,threshVal,threshIneq):
  function buildStump (line 30) | def buildStump(dataArr,classLabels,D):
  function adaBoostTrainDS (line 68) | def adaBoostTrainDS(dataArr,classLabels,numIt = 40):
  function adaClassify (line 98) | def adaClassify(datToClass,classifierArr):

FILE: Decision-Tree/Tree.py
  function calcShannonEnt (line 3) | def calcShannonEnt(dataSet):
  function createDataSet (line 16) | def createDataSet():
  function spiltDataSet (line 26) | def spiltDataSet(dataSet,axis,value):
  function chooseBestFeatureToSplit (line 39) | def chooseBestFeatureToSplit(dataSet):
  function majorityCnt (line 70) | def majorityCnt(classList):
  function createTree (line 78) | def createTree(dataSet,labels):

FILE: DeepLearning/CNN_mnist/cnn.py
  function funcnn (line 24) | def funcnn(LR,BS):

FILE: DeepLearning/CNN_mnist/data.py
  function load_data (line 6) | def load_data():

FILE: DeepLearning/CNN_mnist/trainCNN.py
  function floatrange (line 12) | def floatrange(start,stop,steps):

FILE: GMM/gmm.py
  function gmm (line 18) | def gmm(X,K):
  function inti_params (line 46) | def inti_params(centroids,K,X,N,D):
  function calc_prop (line 62) | def calc_prop(X,N,K,pMiu,pSigma,threshold,D):
  function test (line 73) | def test():

FILE: KNN/KNN.py
  function createDataSet (line 4) | def createDataSet():
  function classify0 (line 10) | def classify0(inx,dataSet,labels,k):

FILE: MLP/dualperceptron.py
  function calInnerProduct (line 22) | def calInnerProduct(i, j):
  function AddVector (line 29) | def AddVector(vec1, vec2):
  function NumProduct (line 35) | def NumProduct(num, vec):
  function createGram (line 41) | def createGram():
  function updateParm (line 50) | def updateParm(k):
  function calDistance (line 56) | def calDistance(k):
  function trainModel (line 65) | def trainModel(Iter):

FILE: MLP/perceptron.py
  function updateParm (line 19) | def updateParm(sample):
  function calDistance (line 25) | def calDistance(sample):
  function trainMLP (line 34) | def trainMLP(Iter):