SYMBOL INDEX (149 symbols across 21 files)

FILE: chapter-2/filteringdata.py
  function manhattan (line 23) | def manhattan(rating1, rating2):
  function computeNearestNeighbor (line 38) | def computeNearestNeighbor(username, users):
  function recommend (line 49) | def recommend(username, users):

FILE: chapter-2/filteringdataPearson.py
  function manhattan (line 23) | def manhattan(rating1, rating2):
  function pearson (line 39) | def pearson(rating1, rating2):
  function computeNearestNeighbor (line 64) | def computeNearestNeighbor(username, users):
  function recommend (line 75) | def recommend(username, users):

FILE: chapter-2/recommender.py
  class recommender (line 42) | class recommender:
    method __init__ (line 44) | def __init__(self, data, k=1, metric='pearson', n=5):
    method convertProductID2name (line 67) | def convertProductID2name(self, id):
    method userRatings (line 75) | def userRatings(self, id, n):
    method loadBookDB (line 93) | def loadBookDB(self, path=''):
    method pearson (line 157) | def pearson(self, rating1, rating2):
    method computeNearestNeighbor (line 185) | def computeNearestNeighbor(self, username):
    method recommend (line 199) | def recommend(self, user):

FILE: chapter-3/adjusted_cosine_similarity.py
  function computeSimilarity (line 17) | def computeSimilarity(band1, band2, userRatings):

FILE: chapter-3/recommender3.py
  class recommender (line 40) | class recommender:
    method __init__ (line 42) | def __init__(self, data, k=1, metric='pearson', n=5):
    method convertProductID2name (line 70) | def convertProductID2name(self, id):
    method userRatings (line 78) | def userRatings(self, id, n):
    method showUserTopItems (line 93) | def showUserTopItems(self, user, n):
    method loadMovieLens (line 101) | def loadMovieLens(self, path=''):
    method loadBookDB (line 161) | def loadBookDB(self, path=''):
    method computeDeviations (line 226) | def computeDeviations(self):
    method slopeOneRecommendations (line 249) | def slopeOneRecommendations(self, userRatings):
    method pearson (line 276) | def pearson(self, rating1, rating2):
    method computeNearestNeighbor (line 304) | def computeNearestNeighbor(self, username):
    method recommend (line 318) | def recommend(self, user):

FILE: chapter-4/classifyTemplate.py
  class Classifier (line 14) | class Classifier:
    method __init__ (line 16) | def __init__(self, filename):
    method getMedian (line 52) | def getMedian(self, alist):
    method getAbsoluteStandardDeviation (line 68) | def getAbsoluteStandardDeviation(self, alist, median):
    method normalizeColumn (line 76) | def normalizeColumn(self, columnNumber):
    method normalizeVector (line 88) | def normalizeVector(self, v):
    method manhattan (line 104) | def manhattan(self, vector1, vector2):
    method nearestNeighbor (line 109) | def nearestNeighbor(self, itemVector):
    method classify (line 114) | def classify(self, itemVector):
  function unitTest (line 119) | def unitTest():

FILE: chapter-4/filteringdata.py
  function manhattan (line 35) | def manhattan(rating1, rating2):
  function computeNearestNeighbor (line 48) | def computeNearestNeighbor(username, users):
  function recommend (line 59) | def recommend(username, users):

FILE: chapter-4/nearestNeighborClassifier.py
  class Classifier (line 51) | class Classifier:
    method __init__ (line 53) | def __init__(self, filename):
    method getMedian (line 89) | def getMedian(self, alist):
    method getAbsoluteStandardDeviation (line 105) | def getAbsoluteStandardDeviation(self, alist, median):
    method normalizeColumn (line 113) | def normalizeColumn(self, columnNumber):
    method normalizeVector (line 125) | def normalizeVector(self, v):
    method manhattan (line 141) | def manhattan(self, vector1, vector2):
    method nearestNeighbor (line 146) | def nearestNeighbor(self, itemVector):
    method classify (line 151) | def classify(self, itemVector):
  function unitTest (line 156) | def unitTest():
  function test (line 188) | def test(training_filename, test_filename):

FILE: chapter-4/normalizeColumnTemplate.py
  class Classifier (line 19) | class Classifier:
    method __init__ (line 21) | def __init__(self, filename):
    method getMedian (line 52) | def getMedian(self, alist):
    method getAbsoluteStandardDeviation (line 68) | def getAbsoluteStandardDeviation(self, alist, median):
    method normalizeColumn (line 81) | def normalizeColumn(self, columnNumber):
  function unitTest (line 95) | def unitTest():

FILE: chapter-4/testMedianAndASD.py
  class Classifier (line 11) | class Classifier:
    method __init__ (line 13) | def __init__(self, filename):
    method getMedian (line 44) | def getMedian(self, alist):
    method getAbsoluteStandardDeviation (line 51) | def getAbsoluteStandardDeviation(self, alist, median):
  function unitTest (line 64) | def unitTest():

FILE: chapter-5/crossValidation.py
  class Classifier (line 13) | class Classifier:
    method __init__ (line 14) | def __init__(self, bucketPrefix, testBucketNumber, dataFormat):
    method getMedian (line 64) | def getMedian(self, alist):
    method getAbsoluteStandardDeviation (line 80) | def getAbsoluteStandardDeviation(self, alist, median):
    method normalizeColumn (line 88) | def normalizeColumn(self, columnNumber):
    method normalizeVector (line 100) | def normalizeVector(self, v):
    method testBucket (line 112) | def testBucket(self, bucketPrefix, bucketNumber):
    method manhattan (line 139) | def manhattan(self, vector1, vector2):
    method nearestNeighbor (line 144) | def nearestNeighbor(self, itemVector):
    method classify (line 149) | def classify(self, itemVector):
  function tenfold (line 155) | def tenfold(bucketPrefix, dataFormat):

FILE: chapter-5/divide.py
  function buckets (line 4) | def buckets(filename, bucketName, separator, classColumn):

FILE: chapter-5/pimaKNN.py
  class Classifier (line 14) | class Classifier:
    method __init__ (line 15) | def __init__(self, bucketPrefix, testBucketNumber, dataFormat, k):
    method getMedian (line 65) | def getMedian(self, alist):
    method getAbsoluteStandardDeviation (line 81) | def getAbsoluteStandardDeviation(self, alist, median):
    method normalizeColumn (line 89) | def normalizeColumn(self, columnNumber):
    method normalizeVector (line 101) | def normalizeVector(self, v):
    method testBucket (line 113) | def testBucket(self, bucketPrefix, bucketNumber):
    method manhattan (line 141) | def manhattan(self, vector1, vector2):
    method nearestNeighbor (line 146) | def nearestNeighbor(self, itemVector):
    method knn (line 151) | def knn(self, itemVector):
    method classify (line 173) | def classify(self, itemVector):
  function tenfold (line 180) | def tenfold(bucketPrefix, dataFormat, k):

FILE: chapter-6/naiveBayes.py
  class Classifier (line 9) | class Classifier:
    method __init__ (line 10) | def __init__(self, bucketPrefix, testBucketNumber, dataFormat):
    method testBucket (line 84) | def testBucket(self, bucketPrefix, bucketNumber):
    method classify (line 115) | def classify(self, itemVector):
  function tenfold (line 134) | def tenfold(bucketPrefix, dataFormat):

FILE: chapter-6/naiveBayesDensityFunction.py
  class Classifier (line 11) | class Classifier:
    method __init__ (line 12) | def __init__(self, bucketPrefix, testBucketNumber, dataFormat):
    method testBucket (line 128) | def testBucket(self, bucketPrefix, bucketNumber):
    method classify (line 160) | def classify(self, itemVector, numVector):
  function tenfold (line 188) | def tenfold(bucketPrefix, dataFormat):
  function pdf (line 229) | def pdf(mean, ssd, x):

FILE: chapter-7/bayesSentiment.py
  class BayesText (line 4) | class BayesText:
    method __init__ (line 6) | def __init__(self, trainingdir, stopwordlist, ignoreBucket):
    method train (line 62) | def train(self, trainingdir, category, bucketNumberToIgnore):
    method classify (line 92) | def classify(self, filename):
    method testCategory (line 114) | def testCategory(self, direc, category, bucketNumber):
    method test (line 130) | def test(self, testdir, bucketNumber):
  function tenfold (line 147) | def tenfold(dataPrefix, stoplist):

FILE: chapter-7/bayesText.py
  class BayesText (line 4) | class BayesText:
    method __init__ (line 6) | def __init__(self, trainingdir, stopwordlist):
    method train (line 61) | def train(self, trainingdir, category):
    method classify (line 86) | def classify(self, filename):
    method testCategory (line 108) | def testCategory(self, directory, category):
    method test (line 119) | def test(self, testdir):

FILE: chapter-8/hierarchicalClusterer.py
  function getMedian (line 9) | def getMedian(alist):
  function normalizeColumn (line 20) | def normalizeColumn(column):
  class hClusterer (line 27) | class hClusterer:
    method __init__ (line 31) | def __init__(self, filename):
    method distance (line 103) | def distance(self, i, j):
    method cluster (line 110) | def cluster(self):
  function printDendrogram (line 189) | def printDendrogram(T, sep=3):

FILE: chapter-8/hierarchicalClustererTemplate.py
  function getMedian (line 9) | def getMedian(alist):
  function normalizeColumn (line 20) | def normalizeColumn(column):
  class hClusterer (line 27) | class hClusterer:
    method __init__ (line 31) | def __init__(self, filename):
    method distance (line 75) | def distance(self, i, j):
    method cluster (line 82) | def cluster(self):
  function printDendrogram (line 88) | def printDendrogram(T, sep=3):

FILE: chapter-8/kmeans.py
  function getMedian (line 12) | def getMedian(alist):
  function normalizeColumn (line 23) | def normalizeColumn(column):
  class kClusterer (line 32) | class kClusterer:
    method __init__ (line 38) | def __init__(self, filename, k):
    method updateCentroids (line 95) | def updateCentroids(self):
    method assignPointToCluster (line 107) | def assignPointToCluster(self, i):
    method assignPointsToCluster (line 123) | def assignPointsToCluster(self):
    method euclideanDistance (line 132) | def euclideanDistance(self, i, j):
    method kCluster (line 139) | def kCluster(self):
    method showMembers (line 159) | def showMembers(self):

FILE: chapter-8/kmeansPlusPlus.py
  function getMedian (line 12) | def getMedian(alist):
  function normalizeColumn (line 23) | def normalizeColumn(column):
  class kClusterer (line 32) | class kClusterer:
    method __init__ (line 38) | def __init__(self, filename, k):
    method showData (line 92) | def showData(self):
    method distanceToClosestCentroid (line 97) | def distanceToClosestCentroid(self, point, centroidList):
    method selectInitialCentroids (line 106) | def selectInitialCentroids(self):
    method updateCentroids (line 139) | def updateCentroids(self):
    method assignPointToCluster (line 152) | def assignPointToCluster(self, i):
    method assignPointsToCluster (line 168) | def assignPointsToCluster(self):
    method eDistance (line 176) | def eDistance(self, i, j):
    method euclideanDistance (line 183) | def euclideanDistance(self, i, j):
    method kCluster (line 190) | def kCluster(self):
    method showMembers (line 210) | def showMembers(self):