Classifier In A Sentence

We found 36 sentences of 'Classifier' to help you understand how to use Classifier in a sentence.

• The classifier in classifier relative clauses can only appear head-initially.
• Animal is used for kingdom classifier.
• In addition, it is also a less effective classifier.
• A distance classifier has been built up for face recognition.
• Turbo air classifier is a important style of accurate classifying facilities.
• Omitting the noun and preserving the classifier is grammatical and common.
• A color based classifier is automatically computed from the control cells.
• Experiments result proves that decision tree classifier is a effective classify method.
• Maximum likelihood classifier ( MLC ) is the most used and effective classification method.
• How to make the classifier adaptive over time becomes a big issue.
• The choice of classifier depends on the semantics of the noun involved.
• Decision trees, neural networks, or a naive Bayes classifier could be used.
• Pattern recognition classifier design, the source for the K - means, after debugging through.
• The full word only includes the pronoun, the number - classifier phrase, the adverb.
• Then a classifier is combined to judge phrases capable of improving the translation quality.
• Bayes classifier model is a powerful tool for classifying attack types in intrusion detection.
• The minimum - distance and neural network classifier are researched on pattern identification in this paper.
• The recognition rates for the handwritten digits and SAR image classification outperform the tradition Bayes classifier.
• Moreover, the design procedure of the pattern recognition is presented and the corresponding pattern classifier is established.
• When the nouns are used with numerals the appropriate classifier word must be included in the phrase.
• Numeral-noun constructions even exist in these languages which have plentiful individual classifier according to the typological linguistic facts.
• In this manner, the overall classifier can be robust enough to ignore serious deficiencies in its underlying naive probability model.
• Thus, to run Mahout's classifier, you need to first train the model and then use that model to classify new content.
• On the design of classifier, by introducing support vector machine, Chinese tone recognition rate is improved under low signal noise rate conditions.
• Extracting frequency features of the ship-radiated noise and constructing classifier applied to object classification and recognition is the main contributiqns in this paper.
• This paper uses the improved K-means (IKM) algorithm to process the missing data and thus improve the precision of the Naive Bayes classifier.
• VTC-90 vertical turbine classifier would bring in a new type equipment featured classification efficiency, stable capability, as well as simple installation and maintenance.
• At last a pattern classifier based on BP neural network is designed to recognize different cracks according to the geometrical shape differences of different cracks.
• Second, the spreader stoker is a size classifier of the fuel and the coarser fuel is fed to the rear requiring more time to burn.
• Naive Bayes classifier is a simple and effective classification method based on probability theory, but its attribute independence assumption is often violated in the real world.
• Based on fuzzy mathematics theory, an edge-detecting algorithm is presented in this paper by combining fuzzy membership functions of GAP and relative entropy coefficient classifier.
• Extracting initial strongly negative data set from positive data and unlabeled data is a base for constructing a PU-oriented text classifier by two stage frame method.
• Algorithm of target classification based on polarization synthesis is proposed, when it is acted as input value of classifier. Then, polarimetric SAR data is applied to classification experiment.
• In practice applications, generic near neighbor classifier was limited for the amount of pattern processing was very large and was difficult to get the best data quickly on line.
• The main idea of which consists of three parts:the discriminating feature analysis of the images, the statistical modeling of face and non-face classes, and the Bayes classifier for face detection.
• In order to solve the problem existing in training data sets, present Bayes algorithm is im- proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.