Classifier In A Sentence

We found 68 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.
• 2 The Nave Bayes' Classifier 1718.
• One of the most difficult points in Chinese text automatic analysis is to analyse and disambiguate classifier and phrase containing classifier.
• NNL classifier has low computation cost and good performance.
• The structure and theory of air classifier was analysised.
• In addition, it is also a less effective classifier.
• In such cases, the classifier should be well-regularized.
• A distance classifier has been built up for face recognition.
• In designing Web Classifier, this thesis makes use of Vector Space Model to represent the web text, which improves the performance of Bayes Classifier.
• This set achieves better performance than each basic classifier taken separately.
• On the national level, there only needs to be one classifier.
• 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.
• The classifier design is a key step for pattern recognition systems.
• 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.
• Constructing an effective text classifier plays a key role in text categorization.
• Recognizing small handwritten character set with this new method and constructing an integrated reorganization system with subspace classifier and BP classifier are the main objects in this paper.
• 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.
• Rather than statically declare the subsumption relations in a knowledge-base a classifier allows the developer to simply declare facts about the world and let the classifier deduce the relations.
• 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.
• Bayesian classification and the back of the linear, non - linear classifier belong to supervised learning.
• The minimum - distance and neural network classifier are researched on pattern identification in this paper.
• The original optimal hyperplane algorithm proposed by Vladimir Vapnik in 1963 was a linear classifier.
• Then, using support vector machine classifier to conduct quality classification on speed ratio control valve.
• The recognition rates for the handwritten digits and SAR image classification outperform the tradition Bayes classifier.
• Then the leakage points were recognized and positioned via weighted minimum distance classifier and neural network.
• 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.
• A decision-making model and a numerical approach of partner selection were proposed based on multiple classifier fusion rules.
• 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.
• Pointing to the classification problem of Web pages, this paper proposes a classification algorithm combining rough set and Bayes classifier.
• The classifier is found in no other language family, although may be present in the Yeniseian family per Vajda ( 2010 ).
• 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.
• Recognition completes the classification which classifies the above-mentioned character vector by classifier which gets the final result by decision-making function.
• It does not have to design the complexity classifier in the traditional recognition algorithm after feature extraction, and simplifies the recognition process.
• We have constructed a simple sub domain classifier that is based on a naive Bayesian approach and trained on the available ETD data.
• 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.
• Besided, features like data classification through statistical analysis of trained sentences and native language processor integrated Naive Bayes classifier are claimed to be inspiring.
• 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.
• Further, a hybrid BP algorithm with dead interval of error is derived for training the neural classifier in order to increase training speed and classification accuracy.
• 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.
• The concept of attribute similarity is presented to solve the weight problem of multi-dimension object classification, and cloud classifier based on attributes similarity is presented also.
• Aim at the document image with both Chinese Characters and English characters, this paper present a character segmentation and language discrimination method based on Simple Bayes Classifier.
• In imbalanced datasets, where the sampling ratio does not follow the population statistics, one can resample the dataset in a conservative manner called LDA classifier with Gaussian distributions.
• 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.
• A new ECG pattern classifier with Variable Area Template is applied to improve the quantity of ECG analysis results, while the optimized software design ensures the other performances.
• 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.
• Decision tree classifier is an important data mining problem. The key issue in constructing the decision tree on data streams is to derive the best criterion of internal nodes.
• It was the highlights of the paper that the method combined the explicit features and naive bayes classifier together to identify both of the encrypted and not encrypted P2P traffic.
• The invariant moment minimum distance classifier is used to complete the vehicle-logo recognition and the experiment result shows that the accuracy of the object recognition is improved by 20 percent.
• 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.
• A reliable and valid AUC estimate can be interpreted as the probability that the classifier will assign a higher score to a randomly chosen positive example than to a randomly chosen negative example.