Introducing Machine Learning

Index

A

acceptance testing, 58

accuracy of data, 71

activation functions, 257–258, 274–277

linear, 274

ReLu, 276–277, 302

sigmoid, 261–262, 274–275

softmax, 275

step function as, 260

TanH, 275–276

adaptability to change, 15–16

adaptive boosting, 204–206

agglomerative hierarchical clustering, 40

agility in artificial intelligence (AI), 348

AI. See artificial intelligence (AI)

algorithms. See also models

for classification, 34–36

KNN algorithm, 230–234

SVM algorithm, 235–245

for clustering, 39–40

DBSCAN, 248–251

K-Means, 246–247

K-Modes, 247–248

decision trees

for classification, 186–193

design principles, 185

expert systems versus, 185

for regression, 194–195

ensemble methods, 198

bagging technique, 198–203

boosting technique, 203–210

for linear ...