Here I train a naive bayes algorithm nb <- naive_bayes(formula, data = train) plot(nb) nb.pred <- predict(nb, test) nb.test <- predictedReturn(test, nb.pred) plot(nb.test$prediReturn, type = "line") plot(nb.test$cumReturn, type = "line") confusionMatrix.nb <- table(nb....
Nevertheless, the Naive Bayes algorithm has been shown time and time again to perform really well in classification problems, despite the assumption of independence. Simultaneously, it is a fast algorithm since it scales easily to include many predictors without having to handle multi-dimensional corre...
Naive Bayes is a classification algorithm. Traditionally it assumes that the input values are nominal, although it numerical inputs are supported by assuming a distribution. Naive Bayes uses a simple implementation of Bayes Theorem (hence naive) where the prior probability for each class is calculate...
naive BayesTo explore the adoption of artificial intelligence (AI) technology in the field of teacher teaching evaluation, the machine learning algorithm is proposed to construct a teaching evaluation model, which is suitable for the current educational model, and can help colleges and universities to...
logistic activation functions in a multi-layer neural network, we’ll lose this convexity. Looking only at a single weight / model coefficient, we can picture the cost function in a multi-layer perceptron as a rugged landscape with multiple local minima that can trap the optimization algorithm:...
Naïve Bayes algorithm was adopted for a specific amount of water according to the crop needs. By adopting this proposed method, proper water management can be achieved. In a different study, researchers (Xie et al., 2017) suggested a framework to support irrigation systems. The framework ...
While thousands of algorithms are available to uncover hidden patterns, trends, and relationships in various types of content, the most popular ones are : Naive Bayes Classifier: It’s a probabilistic classifier used in high-dimensional training datasets ...
Still use NaiveBayes as the classifier. 1. Use “CfsSubSetEval” as attribute evaluator and choose “Bestfirst” with “Forward” direction as your search method. Run your classifier and record the names of selected attributes and the Question 2...
(SVM) with Linear kernel, SVM with Radial Basis Function (RBF) kernel, Naïve Bayes (NB), and Generalized Linear Model (GLM). The DL-based algorithm is Artificial Neural Network (ANN). For the evaluation purpose, we prepare a land cover ground truth (actual) dataset of the City of ...
This investigation was intended to aid the implementation of a classification algorithm for the automatic creation of LULC classification maps. We perform object-based and pixel-based analyses to investigate the ability of the classifiers and their accuracies, respectively. RF had the best ...