Page 204 - Data Science Algorithms in a Week

program arguments 187 implementation 10, 13
for loop visualization 14
about 185
on range 185 L
G level of confidence
measuring 94, 95
genetic algorithms 190 linear regression
gradient descent algorithm about 178
about 140, 141, 143 on perfect data 136, 137
implementation 140 on real-world data 139, 140
models, comparison by R 144 visualization 138
I M
ID3 algorithm map data
about 57 analysis 16, 17
decision tree construction 57, 58 example 15
implementation 58, 64
independent events 33, 34 N
inductive inference 190 Naive Bayes classifier
information entropy about 189
about 53 implementation 34
coin flipping 54 Naive Bayes' theorem
definition 54, 55 about 29
information gain 55 basic application 30, 31
information gain calculation 55 extension 31, 32
information theory 53 proof 31, 32
K Naive Bayes
for continuous random variables 40, 42
k clusters neural networks 190
analysis 113, 117, 118, 119, 120 non-linear model 146, 147, 148
classifying 105, 107, 108
clustering 102, 103 P
in semantic context 119, 123, 126 PageRank 190
selecting 113 principal component analysis 190
k-means clustering algorithm priori association rules 190
about 103, 189 Python reference
centroid, computing 104 about 179
implementation 109 comments 180
initial k-centroids, picking 104 Python Hello World example 179
input data, from gender classification 112
on household income example 104, 105 R
program output, for gender classification data R reference
112
k-nearest neighbors algorithm about 174
about 189 comments 175

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