Different algorithm modules include Artificial Neural Network (ANN), Synthetic Aperture Radar (SAR), Support Vector Machine (SVM), and Decision Tree (DT).Ritik Pratap SinghSaloni SinghRagini Nandan ShakyaShahid EqbalInternational Conference on Emerging Trends and Advances in Electrical Engineering and ...
Naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes’ theorem with strong (naive) independence assumptions between the features. The spark.ml implementation currently supports both multinomial naive Bayes and Bernoulli naive Bayes. ...
Performance analysis of classifiers for EMG signal of different hand movements In this paper, different classification methods have been used to classify the EMG signals. EMG signals have been extracted from five different subjects ... R Dev,AK Singh - 《International Journal of Biomedical Engineering...
classifiers[J]. Machine Learning 1997 29 2/3 131 - 163. @@[3]邓维斌,黄蜀江,周玉敏.基于条件信息熵的自主式朴素贝叶 斯分类算法[J],计算机应用 2007,27 4 888 -891. @@[4] 章舜仲,王树海,黄河燕,等.基于属性相关性分析的贝叶斯分 类模型[J].情报学报,2007,26 2 271 -274. ...
Classification (machine learning): What are the broad categories of classifiers? Which classification algorithms output the most accurate probability estimates? Xavier Amatriain, Netflix Research/Engineering Director... (more) ...
I have total of 6 classes in my dataset (concatenated all activities) and training multiple classifiers and also implementing K-fold cross validation during training. I split my data into train and test set, train my classifier and then test my classifier and accuracies are pretty good (...
classifiers with 97.08% Accuracy, ROC = 0.996, and RMSE = 0.1527. Sensitivity analysis for some of these classifiers was performed to study the performance of the classifier to classify the Epileptic Seizure dataset with respect to some changes in their parameters. Then a prediction of the ...
However, the methods used in both short text and long text are different. General supervised classifiers which are used with a fixed number of attributes... S Sinthupinyo,W Roadrungwasinkul,C Chantan - Iccas-sice 被引量: 6发表: 2009年 加载更多来源...
different classifiers for selected features. The types of classifiers have included an artificial neural network21, k-nearest neighbor16, logistic regression20, naïve Bayes13, random forest3, and support vector machine10. Thus, machine learning-based seizure autodetection was traditionally composed of...
Our research evaluated local recurrence using three machine-learning algorithms, including LR-LASSO, SVM and LDA classifiers. The LR-LASSO algorithm showed the best predictive performance and demonstrated similar predictive ability with the PI-RR assessment of experts. To the best of our knowledge, ...