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When developing a classification model it could be more important to have a high sensitivity for one class at the expense of a greater number of corresponding false predictions.
Random forests [ 12] were used for developing a classification model, as implemented in the randomForest package [ 30] of R. Receiver operating characteristics (ROC) curves were calculated and analyzed using the ROCR package [ 31].
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Cerius2 descriptors were employed to develop a classification model for the 2772 compounds with antipsychotic activity.
Molconn-Z and BCUT topological descriptors were employed to develop a classification model for 1328 dopamine antagonists from MDDR database.
To separate true positives and false positives from the putative PPI dataset, we have developed a classification model based on an alternating decision tree algorithm.
A combination of classification and regression trees with Random Forests analysis was used to develop a classification model for FRI polygons based on patterns of Canada yew abundance, and assess the performance of the model.
The training set is used to develop a classification model to predict cancer features with a cross-validation strategy.
Synchronous fluorescence spectra were collected for each extracted fat sample to develop a classification model.
We developed a classification model for early detection of PCA on the basis of SELDI-TOF MS data using DF.
Also, these properties can be used as a starting point to develop a classification model to determine the category of a new candidate AMP.
The objective of this study was to develop a classification model for the auxiliary diagnosis of IgAN using multiparameter analysis with various biological parameters.
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