algorithms and complexity 1994
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Many previous works have used GA for solving optimization problems of the PSO and this algorithm has been applied to solve various topics of dispatching powers for determining
The three popular decision tree construction algorithms, Id3, C4.5 and Cart have been applied for the problem and it has been observed that trees constructed with C4.5 algorithm has
Table 4: RMSE values of regression algorithms for total deaths prediction Algorithm used Deaths Polynomial regression 0.97 Decision tree 0.15 Random forest 0.14 5 Conclusion This
List of Abbreviations APX The class of polynomial-time constant approximable problems CDS Connected dominating set CLDS Connected liar’s dominating set DS Dominating set DTIME
For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine SVM, Random Forest, and Decision Tree, and one Deep Learning algorithm
ALGORITHM SELECTED FOR COMPARISON 2.1Random Forests Random forests is a idea of the general technique of random decision forests that are an ensemble learning technique for
The results of the experiments carried out in this study the Decision Tree Algorithm C4.5 and Naïve Bayes can be used in modeling the early detection of diabetes.. The highest average
Some supervised machine learning algorithms are: Decision Tree Random Forest Naïve Bayes Algorithm Linear Regression Logistic Regression K – Nearest Neighbor
