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NLP-based detection of systematic anomalies among the narratives of consumer complaints
We develop an NLP-based procedure for detecting systematic nonmeritorious consumer complaints, simply called systematic anomalies, among complaint narratives.
Detecting systematic anomalies affecting systems when inputs are stationary time series
We develop an anomaly-detection method when systematic anomalies, possibly statistically very similar to genuine inputs, are affecting control systems at the input and/or output stages.
Anomaly Detection
Time Series Analysis
Methodology
94A12, 94A13, 62P30, 62P35
Functional Correlations in the Pursuit of Performance Assessment of Classifiers
In statistical classification and machine learning, as well as in social and other sciences, a number of measures of association have been proposed for assessing and comparing individual classifiers, raters, as well as their groups.
