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STARK: Self-Tuning Association Rules for KNIME - A Pascal-2 Harvest Project
Published on Apr 25, 20123583 Views
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Chapter list
STARK: Self-Tuning Association Rules for KNIME A Pascal-2 Harvest Project00:00
Implications: As a data analysis tool - 101:48
Implications: As a data analysis tool - 202:56
Implications: As a data analysis tool - 303:06
Implications: As a data analysis tool - 403:32
Implications: As a data analysis tool - 504:10
The Confidence-and-Support Framework, I:The confidence bound - 104:59
The Confidence-and-Support Framework, I:The confidence bound - 206:45
The Confidence-and-Support Framework, II: The support bound - 107:43
The Confidence-and-Support Framework, II: The support bound - 208:51
As a Data Mining Tool: Associations are not the most successful technology so far10:00
Example: Dataset on Abstracts of PASCAL Reports - 111:36
Example: Dataset on Abstracts of PASCAL Reports - 211:51
Yet Another Example: Dataset on Contraceptive Method Choice12:50
Redundancy in Association Rules: A Logic-based view13:13
Irredundant Rules for Dataset FIMI pumsb-star: Inspires a notion of "novelty"17:01
Closure-Based Confidence Boost: One way through19:17
Parameter-Less, "Self-Tuning" Option: A somewhat bold attempt - 120:41
Parameter-Less, "Self-Tuning" Option: A somewhat bold attempt - 221:14
Parameter-Less, "Self-Tuning" Option: A somewhat bold attempt - 321:29
Parameter-Less, "Self-Tuning" Option: A somewhat bold attempt - 421:31
Parameter-Less, "Self-Tuning" Option: A somewhat bold attempt - 522:19
Parameter-Less, "Self-Tuning" Option: A somewhat bold attempt - 622:20
KNIME: A tool, a community, and a company23:15
STARK: Porting yacaree into KNIME - 128:30
STARK: Porting yacaree into KNIME - 231:39
STARK: Will keep working with KNIME in 2012. . . and hopefully beyond! - 133:50
STARK: Will keep working with KNIME in 2012. . . and hopefully beyond! - 234:23