In particular, I propose a novel approach of KNN classifier over semantically secure encrypted data in the cloud. The proposed protocol protects the confidentiality of data, privacy of user's input query, and hides the data access patterns.Ms.Ashwini R. Garad...
# Create KNN classifier knn = KNeighborsClassifier(n_neighbors=3) # Fit the classifier to the data knn.fit(X_train_std, y_train) # Predict the labels of the test set y_pred = knn.predict(X_test_std) # Print the accuracy of the classifier print(f'Accuracy: {accuracy_score(y_test,...
This paper explores a simple and efficient baseline for text classification. Our experiments show that our fast text classifier fastText is often on par with deep learning classifiers in terms of accuracy, and many orders of magnitude faster for training and evaluation. We can train fastText on mo...
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It is therefore necessary to implement the classifier chain method. However, this method will affect the experimental results with the order of tags. 2.2. The whole process A general description of how to solve the problem of multi-label classification of social media users can be found in Fig...
Our experiments show that our fast text classifier fastText is often on par with deep learning classifiers in terms of accuracy, and many orders of magnitude faster for training and evaluation. We can train fastText on more than one billion words in less than ten minutes using a standard multi...
A new distance-weighted k-nearest neighbor classifier. J. Inf. Comput. Sci. 2012, 9, 1429–1436. [Google Scholar] I-Smart, Power Planner, Kepco. Available online: https://home.kepco.co.kr/kepco/main.do (accessed on 7 September 2022). Martínez, F.; Frías, M.P.; Pérez-Godoy, M...
The correlation between image areas and annotations was learned using a multilabel semantic learning model based on the Bayes classifier which was then applied to predict labels for nonannotated images. In [18], region-based bag-of-words (RBoW) was used for sparse feature aggregation, and the ...
As an instance based learning method in pattern recognition, the KNN classifier can sort each element of a study case on account of its nearest training examples in the feature space. For instance, to classify a sample Si, the algorithm first searches for its K nearest neighbors in the ...
Keywords: diabetes; monitoring system; KNN classifier algorithm; ubiquitous healthcare Sensors 2010, 10 3935 1. Introduction The use of ubiquitous computing in healthcare service is being actively studied to promote health by implementing systems that will improve the quality of life [1-3]. The ...