Index

  • Abhaya, 425
  • Absolute rarity, 350, 353
  • Access circumstance, 155
  • AI, 324
    • DM algorithm, 337
    • hand detection, 340
    • machine learning, 338
    • visual information, 329
  • Algorithms,
    • artificial neural network, 84
    • bagging, 84
    • Bayesian classifier, 83
    • boosting, 84
    • classifier, 82
    • clustering technique, 84
    • decision tree, 82
    • denoising, 82
    • dimension reduction, 82
    • ensemble classifier, 84
    • instance-based classifier, 82
    • kNN classifier, 82
    • logistic regression, 83
    • rule-based classifier, 82
    • sampling, 81
    • support vector machine (SVM), 83
  • ANN, 452
  • ARM regulator, 427
  • Artificial intelligence, 268
  • Artificial intelligence (AI) model, 437
  • Artificial neural network algorithms, 375
  • Assessment, 310
  • Association rule learning algorithms, 375
  • Atmosphere science, 41
  • Bayesian algorithms, 373
  • Bayesian classifier, 239
  • Big data, smart grids, 256
  • Blog, 37
  • Brain signal, 398
  • Brute-force, 351
  • Business understanding, 155
  • Cancer, 349–350
  • CART, 449
  • Case-based algorithms, 370
  • Challenges in recommender system (RS),
    • cold start problem, 65
    • correctness, 66
    • diversity, 66
    • gray sheep, 66
    • novelty, 65
    • over specialization, 66
    • privacy, 66
    • scalibility, 66
    • serendipity, 65, 78
    • shilling attack, 66
    • sparsity problem, 65
    • stability, 66
    • usability, 66
    • user preference, 66
  • CHB-MIT, 400
  • Classification, 7
  • Clean data, 158
  • Cloud, 245
  • Clustering, 129
  • Clustering, 7
    • fuzzy, 8
    • hierarchical, 8
    • K-means, 8
  • Clustering algorithms, 374
  • Cognitive integration, 243
  • Complex datasets, 27
  • Concept drift, 103
  • Confusion matrices, 202
  • Content difference, 78
  • Contrastive divergence, 409
  • ConvLSTM design, 430
  • Convolutional network, 436
  • COVID-19, 447
  • CRISP-DM, 450
  • Crop monitoring, 42
  • Cyber physical system (CPS), 236
  • Data, 59
  • Data analytics, 178
    • descriptive analytics, 178–179
    • diagnostic analytics, 178–179
    • perspective analytics, 178–179
    • predictive analytics, 178–179, 180
  • Data association, 130
  • Data attack, 153
  • Data classification, 129
  • Data collection, 153
  • Data conversion, 154
  • Data exploration, 202
  • Data illustration, 154
  • Data mining, 1, 3, 126, 154, 210, 449, 451
    • algorithms, 7
    • application of, 3
    • importance of, 3
    • issues, 6
    • techniques, 10
    • tools, 11
  • Data mining applications, 166
  • Data mining assignments, 378
  • Data mining framework, 199
  • Data mining, defined, 22
  • Data mixing, 153
  • Data partitioning, 203
  • Data preparation, 158
    • combine information, 295
  • Data pre-processing, 196
  • Data protection and morals, 27–28
  • Data reduction, 101
    • sampling, 101
    • sketching, 102
  • Data regression, 130
  • Data sympathetic,
    • confirm data quality, 292
    • data excellence description, 292
    • investigate facts, 291
    • portray data, 291
  • Data understanding, 156
  • Data warehouse, 9
  • Data, classification and mining behavior of,
    • introduction, 22–23
    • mining dynamic/streaming data, 23–24
    • mining graph & network data, 24–25
    • mining heterogeneous/multi-source information, 25–28
    • mining high dimensional data, 28
    • mining imbalanced data, 29
    • mining multimedia data, 30–34
    • mining scientific data, 34–35
    • mining sequential data, 35–36
    • mining social networks, 36–40
  • Databases, 4
  • Decision tree, 215
  • Decision tree algorithms, 372
  • Decision trees, 10
  • Deep learning, 400, 452
  • Deep learning algorithms, 376
  • Deployment, 162
    • audit venture, 302
    • plan arrangement, 301
  • Design evaluation, 154
  • Determine business objectives,
    • evaluate the current circumstance, 288
    • realizes data mining goals, 289
  • DH-DLNN, 197
  • Dimensionality reduction algorithms, 377
  • Distribution, 310
  • Ecological knowledge, 42
  • EEG, 400
  • Ensemble algorithms, 378
  • Entropy, 197
  • Epilepsy, 398
  • Euclidean separation, 48
  • Evaluation, 160
    • survey measure, 299
  • Evaluation measures,
    • controlling variable, 79
    • F-measure, 81
    • generalization power, 79
    • hypothesis, 79
    • mean absolute error, 80
    • normalized distance-based performance measure (NPDM), 81
    • precision, 80
    • prediction accuracy, 79
    • recall, 81
    • root mean square error (RMSE), 79
  • Facebook, 37, 39–40
  • Fault recommendation systems, 240
  • Fightback, 426
  • Fightback application, 426
  • Fleeting, 40, 41, 42
  • Fuzzy choice tree, 229
  • Fuzzy clustering, 135
  • Generalization, 357–358
  • Genetic algorithms, 10
  • Genre accuracy, 78
  • Gibbs sampling, 409
  • Gini index, 217
  • Glympse, 426
  • Google, 39
  • Google map pin, 439
  • HCI, 450
  • Heat maps, 430
  • Heliophysics, 43–44
  • High dimensional data mining, 28
  • Human computer interaction (HCI), 317
    • COMPUTER, 319
  • Human robot collaboration (HRI), 321
    • data mining, 323
  • Hybridization method (HM),
    • cascade, 69
    • feature combination, 69
    • meta-level, 77
    • mixed, 77
    • switching, 77
    • weighted, 77
  • Ictal, 403
  • Imbalanced data mining, 29
  • Inductive learning, 211
  • Intelligent safety system for women security, 427
  • Investigate data, 158
  • IoT, 247
  • IT service management (ITSM), 176–177
  • IT services, 176
  • KDD, 2, 448
  • Kernel trick, 83
  • K-mean, 138
  • K-means calculation, 50
  • K-nearest neighbors, 227
  • KNIME, 13
  • Knowledge discovery in data (KDD), 22
  • Knowledge discovery in database (KDD), 2, 126
  • Knowledge indexes, 40
  • Landsat 7
  • instrument, 34
  • L-design, 36
  • Logistic regression, 200
  • LTM, 220
  • Machine learning, 451
  • Machine learning algorithms, 368
  • MapReduce, 246
  • MATLAB, 135
  • Matrix factorization, 57, 77
  • MAX 232, 427
  • Melanoma, 350
  • Metadata design, 22
  • Methodology, 167
  • Misclassification rate, 202
  • Mobile-based women safety application, 427
  • Model learning, 59
  • Model process life cycle, 201
  • Modeling, 158
    • association rule mining or association analysis, 307
    • classification algorithms, 307
    • clustering algorithms, 308
    • evaluation model, 297
    • fabricate ideal, 297
    • produce an investigation plan, 297
    • regression algorithms, 308
    • select displaying strategy, 296
  • Movie elasticity, 78
  • Multidimensional databases, 212
  • Multimedia data mining, 30–34
    • common applications, 31
    • multimedia database management, 32–34
    • utilizations, 31–32
  • Multiple species flocking (MSF), 264
  • Multi-relational data, 26–27
  • Multi-relational information mining, 25
  • Multi-social information digging, 26–27
  • Multi-source and multidimensional information, 26
  • MultiSource Dynamic TrAdaBoost, 359
  • Naïve Bayes, 227
  • NASA Earth Observation System, 34
  • Negative instances, 357
  • Negative-transfer, 352, 361
  • Neural networks, 132, 227
  • Neuroscience, 41–42
  • Nirbhaya, 425
  • NoSQL, 251
  • Object instance segmentation, 454
  • Object recognition, 453
  • OLAP, 228
  • OLTP, 9
  • Online advertising, 37
  • Online media mining, 37
  • Orkut, 39
  • OverFeat, 454
  • PCA, 404
  • Picture mining, 33
  • Pigmented, 358
  • Predictive analytics, 198
  • Pre-processing, 59
  • Processes of data analysis, 153
  • Propensity buy, 201
  • Python, 12
  • Random forest model, 189–191
  • Range and obstacle recognition, 426
  • Rapid miner, 17
  • Rare dataset, 351
  • Raspberry Pi, 427
  • R-CNN, 454–455
  • Reanalysis project, 34
  • Recommender system (RS) types,
    • collaborative filtering, 60, 67
    • content-based, 61, 67
    • demographic, 62, 67
    • hybrid recommender system, 64, 68
    • knowledge-based recommender system, 63, 68
    • utility recommender system, 63, 67
  • Regression algorithms, 370
  • Regularization algorithms, 372
  • Relevance network, 78
  • Restricted Boltzmann machine, 406
  • RFID, 426
  • Safe framework, 427
  • Scientific data mining, 34–35
  • Security framework for women and children,
    • application development, 436–437
    • data selection, 428–429
    • issue and solution, 427–428
    • pre-preparation data, 430–436
    • related work, 424–427
    • use case for the application, 437–440
  • Selection and independent variables, 200
  • Self-preservation framework for women, 426
  • Self-salvation, 427
  • Semi-supervised learning, 369
  • Sequential data mining, 35–36
  • Silhouette, 126
  • Slack variable, 83
  • Social ability, 37
  • Social advertising, 36–37
  • Social networks mining, 36–40
  • Social registration, 37
  • Social media data mining reasons, 39–40
  • Software, 176
  • Sound mining, 34
  • Spatial and temporal data mining, 40–44
  • Spatial-transient (st) data, 40–41
  • Square blunder function, 47
  • STFT, 401
  • STM, 220
  • Stochastic gradient, 408
  • Stream applications, 120
  • Stream implementation, 110
  • Stream mining, 99, 448
  • Stream mining operations, 105
    • classification, 106
    • frequent itemset mining, 108
    • outlier detection, 107
    • stream clustering, 105
  • Stream processing system, 100
  • Stream tools and techniques, 109
  • Stun firearm application, 426
  • Testing and validation, 60
  • Text mining, 33
  • Ticket analytics, 181
    • client 1, 185
    • client 2, 185
    • healthcare sector, 186
    • predictive modeling, 188
    • sample analyses, 182–184
  • Ticketing system, 181
  • TrAdaBoost, 351
  • Traffic dynamics, 43
  • Transfer learning, 351
  • TrResampling, 353
  • Tumor, 350
  • Twitter, 40
  • Unsupervised learning, 369
  • User elasticity, 78
  • Video mining, 33
  • VithU application, 426
  • Wald chi-square, 204
  • Web indexes, 22
  • Web journals, 40
  • Web mining, 163
  • Web-based media, 43
  • Web-based media mining, 36–40
  • Weighted majority algorithm, 355
  • Wireless sensor networks, 259
  • Women empowerment, 425
  • WoSApp, 424
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