what are the difference between clustering and cross enrollment
Clustering refers to the grouping of students enrolled to different schools and taking up the same NSTP component into one group under the management and supervision of a designated school while cross enrollment refers to a system of enrollment where a student is officially enrolled in and academic program of an origin ..
Clustering can be done by grouping of students enrolled to different schools and taking up the same NSTP component into one group under the management and supervision of a designated school while cross enrollment can be done to a system of enrollment where a student is officially enrolled in and academic program of an origin school but is allowed to enroll in the NSTP component of another accepting school. CAPUNKA, CAMSAHAMNIDA:>
Classification is a type of supervised learning (Background knowledge is known) and Clustering is a type of unsupervised learning(No such knowledge is known).
December
To determine the dollar amount of total variance attributed to Enrollment Variance, you would need to calculate the difference between the actual enrollment figures and the budgeted or expected figures, then multiply that difference by the revenue or cost per enrollment. This will yield the Enrollment Variance in dollar terms. The exact amount can only be provided with specific enrollment and financial data.
see zyxo.wordpress.com/2010/07/17/the-difference-between-segmentation-and-clustering/ for a neat explanation.
5% The difference in enrollment is 28 students. 28/560 = 0.05 You use 560 because that was the ORIGINAL enrollment.
Type your answer here... clustering?
Clustering algorithms may be classified as listed below:Exclusive ClusteringOverlapping ClusteringHierarchical ClusteringProbabilistic Clustering
I've been looking for this aswer about a few months, and nothing! Researching on it, I believe that both are same. But, with only one markable difference: clustering is a type of unsupervised learning, and classification is a type of supervised learning. I believe that it is the only difference, and, of course, this dictates the way that the algorithm starts. But the results are essentially similar: grouped data.Good luck in your question. I hope I've helped!
Clustering is a group of resources trying to achieve the same objective, whereas load balancing is having several different servers that are completely unaware of each other and trying to achieve the same objective.