… Process begins from a pre-processing phase followed by feature selection phase based on
DT entropy, classification of modelling performance evaluation, and hyperparameter tuning …

… uses different layers of neural network that decide classification … , we study and compare
among different machine learning … classification of disease, we use machine learning and deep …

… This research work focuses classification of various attacks … deep learning based system.
They design their architecture for classifying the intrusion by arranging the anomaly detection in …

… Section 2 describes the design of the proposed generative model for the classification of
MG faults with its required material. Section 3 presents the performance analysis of the …

… 1: data collection, data preprocessing and features extraction (data representation), model
training, and performance evaluation based on the classification objectives. The paper …

… supervised and unsupervised text classification algorithms for mining the … The various
applications of text classification are sentiment analysis, fraud detection, and spam detection etc. …

… definitions, classifications, modelings, performance evaluation methodologies, … detection.
Hence, in this survey, we present a comprehensive study of the deep learning-based methods …

… study on various existing Machine Learning and Deep Learning-based classification models
proposed by different … crops in terms of their performance evaluations, the dataset used, and …

… the implementation of various machine learning algorithms such as classification and
clustering. It also provides specialized modules such as feature extraction and, model review. Scikit…

… machine learning classification algorithms for securing IoT against DoS attacks. A comprehensive
study … In this section, a detailed discussion on performance analysis of ensembles (RF, …