Sentence examples for multiple feature selection from inspiring English sources
In order to solve the problem, this paper proposes a hybrid model which combines multiple feature selection models to select the most significant input features from all potentially relevant features.
Another item to note is that throughout these studies only one feature selection technique was tested with minimal overlap; therefore, future work should look to test multiple feature selection techniques in order to find which one works the best with medical data.
Thus, multiple feature selection methods were used for generating candidate feature sets.
The data integration approach was suggested by utilizing multiple feature selection methods such as Principal Component Analysis (PCA), PLS, and LASSO [ 18].
Indeed, recent research efforts attempt to combine multiple feature selection techniques, instead of using a single one, in order to overcome the intrinsic limitations of each technique and obtain a more reliable "consensus" result (e.g., a consensus ranking or a consensus subset containing the most frequently selected features).
In fact, one may also see this face-selectivity of the N1 as reflecting multiple overlapping feature selection processes.
Specifically, we proposed a novel ℓ2,1 norm balanced multiple kernel feature selection (ℓ2,1 MKFS), and designed a proximal based optimization algorithm for efficiently learning the model.
To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization.
The inputs of this neural network are theoretically derived descriptors that were chosen by genetic algorithm (GA) and multiple linear regression (MLR) feature selection techniques.
Although a lot of research is going on combining the multiple feature sets, still the selection of complementary feature sets for fusion and the techniques for combining these divergent feature sets are a challenge.
This pipeline ran multiple chains for both feature selection and cross-validation.
