A COMPARISON OF VARIOUS MACHINE LEARNING ALGORITHMS FOR WHEAT SEED DATA SET CLASSIFICATION
Full text
Figure
Related documents
prediction model (HPM), utilizing K-means clustering algorithm directed towards validating a chosen class label of given data sets and also, C4.5 machine learning algorithm
The results showed that the accuracy rate of the random forest model was better by 0.004%, with the label encoder not being applied to the target class, and the label encoder had
The lower performance of the literature mining analysis on this dataset could result from the lower number of available samples (77 samples in relation to 102 for the prostate
On the left is the histogram of classifier favored events given different number of observations: from 1 (top-left corner) up to 26 (bottom-right corner). The input is represented
Discuss and compare model results Define performance indicators to compare models Develop prediction models using regression and classification Collect explanatory data