November 2019
Beginner to intermediate
608 pages
16h 33m
English
book
Data Mining for Business Analytics
by Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel
Content preview from Data Mining for Business Analytics
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Index
- A–B testing, 327
- A–B tests, 334
- accident data
- activation function, 287
- additive seasonality, 432
- adjusted-R2, 171, 172
- affinity analysis, 16, 345
- agglomerative, 379, 387
- agglomerative algorithm, 387
- aggregation, 77, 78, 83, 86
- AIC, 171, 264
- airfare data
- multiple linear regression, 181
- Akaike Information Criterion, 171
- algorithm, 9
- ALVINN, 284
- Amtrak data
- Amtrak ridership example, 453
- analytics, 3
- antecedent, 348
- appliance shipments data
- Apriori algorithm, 345, 349
- AR models, 437
- AR(1), 438, 439
- area under the curve, 140
- ARIMA models, 437
- artificial intelligence, 5, 9, 100
- artificial neural networks, 284
- association rules, 16, 18, 345, 346
- asymmetric cost, 27, 149, 541
- asymmetric response, 541
- attribute, 9
- AUC, 140
- Australian wine sales data
- Auto posts, 512
- autocorrelation, 423, 433, 438
- average linkage, 390, 393
- average squared errors, 165
- back propagation, 290
- backward elimination, 172, 264
- bag-of-words, 497, 501
- bagging, 243, 331
- balanced portfolios, 376
- bar chart, 65
- batch updating, 291
- bath soap data, 537
- benchmark, 127, 145
- benchmark confidence value, 351
- best subsets, 44
- betweenness in a network, 481
- bias, 36, 170, 318
- bias–variance ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.