Classification of new data with the classifiers
Graph Embedded One-Class Classifiers for media data classification
... available in the UCI repository [44]. One-class versions can also be downloaded from Pattern Recognition Laboratory, Netherlands, using the DDtools library [25], which is the case in the present paper. Each dataset ...
43
A Real Time Spam Classification of Twitter Data with Comparative Analysis of Classifiers
... Department of Computer Science & Engineering Department of Computer Science & Engineering Sri Sai University, Palampur, India Sri Sai University, Palampur, India Abstract In today’s scenario, online networking is fast ...
6
Combining Probabilistic Classifiers for Text Classification
... Probabilistic classifiers are considered to be among the most popular classifiers for the machine learning community and are used in many ...probabilistic classifiers exhibit very good performance ...
6
Question Classification using Multiple Classifiers
... other classifiers, especially those of dependency structure rectified by Bi-gram ...single-feature classification into full use to secure greater accu ...
7
Text Classification and Classifiers: A Comparative Study
... automatic classification of data and textual data gains increasingly and give high ...learning classifiers are described ...text data into pre define class. This paper surveys of text ...
5
IN most approaches to binary classification, classifiers are
... (NP) classification, statistical learning ...binary classification, classifiers are designed to minimize the probability of ...to classification in this context inspired by classical ...
14
Training Effective Node Classifiers for Cascade Classification
... Cascade classifiers are widely used in real- time object ...overall classification error rate, a classifier in each node of the cascade is required to achieve an extremely high detection rate and moderate ...
24
Novel methodologies for improving fuzzy classifiers: dealing with multi-class and big data classification problems
... Big Data classification problems, fuzzy rule-based classifiers have not been able to maintain the good trade-off between accuracy and interpretability that has characterized these techniques in non- ...
174
Comparative Analysis of Multiple classifiers for Heart Disease Classification
... learning classification models trained with the optimal subset of features of Parkinson’s disease data set for efficient Parkinson’s disease ...learning classifiers and found that Genetic Algorithm ...
6
Bagged Ensemble Classifiers for Sentiment Classification of Movie Reviews
... work, new combined classification methods are proposed using bagging classifier in conjunction with NB, SVM, GA as the base learners and the performance comparison has been demonstrated using movie reviews ...
11
Multiple Kernel based KNN Classifiers for Vehicle Classification
... a new classification algorithm is developed which classify 2 wheeler, 3 wheeler, LMV and ...KNN classifiers are ...training data sets and based on majority vote, classification is done ...
7
Using holistic features for scene classification by combining classifiers
... Scene classification is a useful, yet challenging problem in computer ...scene classification are the image representation and the choice of the classifier used for decision ...a new technique for ...
8
Ensembles of Sparse Multinomial Classifiers for Scalable Text Classification
... face new challenges in scalabil- ity to large-scale ...Text Classification evaluation (LSHTC3) evaluated systems for multi-label hierarchical categorization of Wikipedia ...several new modeling ideas ...
11
An Ensemble Learning Method for Text Classification Based on Heterogeneous Classifiers
... heterogeneous classifiers can improve model classification ...base classifiers, compares and analyzes changes in the accuracy of base classifiers and integrated models, and then integrates ...
5
Classification of Various Skin Lesions using SVM and KNN Classifiers
... facilitate classification such as general color statistics, contour shape, and texture ...The classification process determines the type of skin lesions from the extracted image ...pattern ...
6
Banana Maturity Classification Using Hybrid Features On Various Classifiers
... Maturity Classification Using Hybrid Features On Various Classifiers ...ripeness classification using Histogram of Oriented Gradients (HOG), zernike and resnet ...(RF) classifiers are ...
12
Classification of Travertine Tiles with Supervised and Unsupervised Classifiers and Quality Control
... c-means classifiers in the classification ...supervised classification algorithm is one of the most important elements that provides success in the data ...pre-trained data is the most ...
6
Waterfall Traffic Classification: A Quick Approach to Optimizing Cascade Classifiers
... The selection criteria are designed to skip ineligible classifiers quickly. For example, in order to implement a module that identifies traffic by analyzing the packet payload sizes, the criterion could check if ...
16
Combining shape-based and gradient-based classifiers for vehicle classification
... vehicle classification with omnidirectional ...gradient-based classifiers outperforms the individual classifiers or ...shape-based classification, we extract features from the silhouettes in ...
6
Lane Change Prediction Using Gaussian Classification, Support Vector Classification and Neural Network Classifiers
... the classifiers is derived from the trajectory by selecting a subset of the features: lateral and longitudinal position coordinates, longitudinal acceleration, and ...the classification had been ...
7