Sentence examples for addresses the classification from inspiring English sources
In[7], a method is presented to determine the encoder of MP3 data on the basis of statistical features extracted from the data; the work also addresses the classification of MP3 files recompressed with different encoders but considering the same value of bit-rate for the second compression.
> Since this task addresses the classification of sentences which are usually much shorter than paragraphs or the whole articles, the bag-of-words features from a local sentence tend to have high risk of data sparseness (18), which could result in a biased representation for low-frequency words and degrade the classification performance.
This study addressed the classification of multi-temporal satellite data from RapidEye by considering different classifier algorithms and decision fusion.
In this paper, we introduces an alternative implementation technique for SVM to address the classification problem with small-size training sample set.
Liwicki et al. [9] also addressed the classification of gender and handedness in the on-line mode (which means that the temporal information about the handwriting is available).
However, some papers partially address the classification of pansharpening methods, see [12] for instance, or relate already proposed techniques of more global paradigms [13 15].
– Bioinspired approaches In 'Data feature selection based on Artificial Bee Colony algorithm', Schiezaro and Pedrini present a bioinspired algorithm for feature selection to address the classification problem.
Specifically, we address the classification and feature measurement of multiple beach zones, a topic addressed to a lesser extent by other projects.
This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS.
Open data also helps address the classification problem, again by lowering the cost at which one group attempts to organize their information, and by creating a culture in which classification schemes are themselves shared, remixed, hacked, and subjected to incremental improvement-but also ready to be torn down and rebuilt when the data indicate.
