Sentence examples for more effective features from inspiring English sources
This type of failure is common for example-based regression approaches [11], and hence, it is necessary to extract more effective features that are less sensitive to such appearance variance to reduce the effect of this problem.
The physical participation of Complete, as attendants or masked ghostly figures, is among the simpler and more effective features of James Ngcobo's inconsistent direction.
In future work, we should set assumptions more strictly or extract more effective features for detecting small motions.
We empirically show that, by going to deeper layers, our model is able to generate more effective features with refined discriminative power.
begin{aligned} MS_W = frac{ sum _{ij}( x_{ij} - bar{x_i })^2 }{ n - m } end{aligned} (4 By extracting more effective features based on F-test scores, we examined whether ANOVA feature selection improves the accuracy of the classification methods.
The number of mixtures is set to 4. In this paper, we explored more effective features for the classification of neutral and stressed speech based on a physical model.
A much more effective feature is the volume control, which makes all of the songs play back at about the same volume level regardless of the level at which they were recorded.
The B-MC-ELM-AE algorithm is then implemented on the SIF features for each frame to learn more effective feature representation, which will generate multiple-channel bilinear features.
The comparison and analysis of classification complexity are made between the two measures and it is indicated that neighborhood-tolerance conditional entropy is a more effective feature evaluation criterion than dependency in incomplete decision table.
In concrete, the more effective feature set will be the one that gives a lower upper bound of the Bayes error, interpreting this value as a measure of class separability.
In a study by Lu et al. [ 52], the investigators integrated data types in order to perform more effective feature selection: they identified 475 genes that were differentially expressed between lung adenocarcinoma and normal tissue, and that were also located in copy number varying regions.
