An ANN Based Approach for Software Fault Prediction Using Object Oriented Metrics

Kaur, Rajdeep; Sharma, Sumit

doi:10.1007/978-981-13-3140-4_31

Cited by 7 publications

(1 citation statement)

References 45 publications

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“…Artificial Neural Network-Multi-Layer Perceptron: As the most extensively used machine learning algorithm [21], Artificial Neural Network (ANN) is characterized with various types which has been employed in various aspects of research [21]. One of such is the Multi-Layer Perceptron (MLP).…”

Section: Modelsmentioning

confidence: 99%

Rainfall Prediction Using Machine Learning Algorithms for the Various Ecological Zones of Ghana

et al. 2022

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Accurate rainfall prediction has become very complicated in recent times due to climate change and variability. The efficiency of classification algorithms in rainfall prediction has flourished. The study contributes to using various classification algorithms for rainfall prediction in the different ecological zones of Ghana. The classification algorithms include Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Extreme Gradient Boosting (XGB) and K-Nearest Neighbour (KNN). The dataset, consisting of various climatic attributes, was sourced from the Ghana Meteorological Agency spanning 1980 -2019. The performance of the classification algorithms was examined based on precision, recall, f1-score, accuracy, and execution time with various training and testing data ratios. On all three training and testing ratios: 70:30, 80:20 and 90:10, RF, XGB and MLP performed well, whereas KNN performed least across all zones. In terms of the execution time of the models, Decision Tree is consistently portrayed as the fastest, whereas MLP used the most run time.

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Section: Modelsmentioning

confidence: 99%