How does the choice of the number of trees and other hyperparameters affect the performance of a Random Forest based on J48-like trees?

Feb 25, 2022 ... ... J48 algorithms are used. As for the feature selection algorithm; Gain Ratio Attribute and ReliefF Attribute are selected. The results are ... Class J48 · Field Summary · Fields inherited from class weka.classifiers.AbstractClassifier · Fields inherited from interface weka.core.Drawable · Constructor ... In this sense, the performance of the proposed methodology was evaluated in a comparative way between the Random Forest and the type J48. Decision Tree. For ... [16] data can be collected by different means like by using distributed questioner also; LR, J48, and ANN. Decision Tree classification technique gave better ... Oct 1, 2019 ... In this paper J48 and Random Forest (RF) machine learning algorithms are used for classification of cyber threats using NetFlows. The results ... The decision tree J48 algorithm is used for the C4.5 algorithm in the ... 5 algorithm is presented using decision tree J48. Figure 1 Decision tree of ... Java implementation of the C4.5 algorithm is known as J48, which is available in WEKA data mining tool. Gain Ratio. Where: |Dj|/|D| acts as the weight of the ... Laxmikant Dewangan, Mausami Kar, “Classification of epileptic EEG signals based on J48 Classifier based feature selection”, (Published by IJRASET, INDIA) ... Jul 7, 2024 ... Algorithm: J48, an extension of ID3 algorithm, also known as C4.5. Outcome: Construct a decision tree structure to classify data. Key Concepts. Evaluating the performance of the J48 decision tree. Description. This function evaluates the performance of the generated trees for error estimation by ...