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Constrained Logistic Regression for Discriminative Pattern Mining
Published on Nov 29, 20112992 Views
Analyzing differences in multivariate datasets is a challenging problem. This topic was earlier studied by finding changes in the distribution differences either in the form of patterns representing c
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Chapter list
Constrained Logistic Regression for Discriminative Pattern Mining00:00
Overview00:19
Introduction00:26
Real Life Examples01:15
Challenges02:39
Existing Approaches03:28
Need for Constrained Models04:24
Goals05:26
Contributions06:08
Notations06:39
Logistic Regression07:18
Logistic Regression cont.07:55
Supervised Distribution Difference08:36
Overall Approach09:04
Constrained Optimization09:59
Constrained Logistic Regression11:35
Synthetic Datasets I (SD I)12:41
Synthetic Datasets II (SD II)13:20
Real World Datasets (RWD)13:39
Sensitivity of Distance Metric13:39
Synthetic Datasets II (Sensitivity)13:56
Real World Datasets Sensitivity14:06
Conclusion and Future Works14:29
References14:56
Thank You15:01