Sentence examples for sequence classifier from inspiring English sources

A sequence classifier, is a mapping, such that corresponds to the predicted label, or classification decision, for the observed sequence.

An augmented TDNN (ATDNN) which builds frequency and scale induction functionals into TDNN is then developed and proved to be a frequency and scale invariant sequence classifier.

The proposed algorithm, MOSC (Multi-Objective Sequence Classifier), is compared to standard classifiers and previous works on these real data sets and exhibits noticeably better classification performance.

In this first study, we have shown how the gene sequence classifier Strand can be used to predict multiple classes of polymorphic malware using data provided by the Kaggle Microsoft Malware Classification Challenge (Big 2015).

Whereas most gene classification tools are optimized for and restricted to an alphabet of four letters (nucleic acids), we have selected the Strand gene sequence classifier for malware classification.

KEF's statistical named entity recognizer (NER) annotator can also use the Stanford NER tagger to tag people, organizations, and locations based on a linear chain Conditional Random Field sequence classifier.

We selected Strand because, unlike the aforementioned gene sequence classifiers, it can process sequences of arbitrary alphabets.

From the success of this demonstration, we conclude that gene sequence classifiers in general, and Strand in particular, hold great promise in their application to security datasets.

We use comparatively, two feature sequence classifiers, that is, Hidden Markov Models (HMM) and Hidden Conditional Random Fields (HCRF), and various feature subspace classifiers, that is, ICA (Independent Component Analysis) and NMF (Non-negative Matrix Factorization) on the spatiotemporal data.

This is possible since unlike many other sequence classifiers and k-mer counters [16,17,33], Strand uses no special encoding of sequence data and supports any Unicode character within the sequences.

Supervised metagenome sequence classifiers have typically assigned reads and contigs based on similarity to reference genomes.