| 摘要 |
A system and method of generating a generic binary classifier for the presence of one or more toxins in water is provided. Features are extracted from a plurality of normalized a priori data sets that include one or more control data sets that are representative of an electric cell-substrate impedance sensor (ECIS) response to water with no toxins therein, and a plurality of treatment data sets that are representative of an ECIS response to water with a toxin therein. A plurality of classifier algorithms are trained using the extracted features, and a plurality of classification models are generated from each of the trained classifier algorithms. Each of the classification models is evaluated and, based on the evaluation of each classification model, a subset thereof is selected. The selected subset of the classification models is supplied as the generic binary classifier. |
