Cluster analysis is a method of classifying data or set of objects into groups. This method is very important because it enables someone to determine the groups easier. This idea involves performing a Time Impact Analysis, a technique of scheduling to assess a data’s potential impact and evaluate unplanned circumstances.
By the use of Time Impact analysis, Cash Flow Analysis for Small Business appears in the picture, this is a method of examining how the money in your business goes in and out. Cash Flow analysis also involves a Cash Flow Statement that presents the data on how well or bad the changes in your affect your business.
Two Main Types of Clustering
So what is cluster analysis then?
As being said from above, cluster analysis is the method of classifying or grouping data or set of objects in their designated groups where they belong. This method has been used for quite a long time already, in Psychology, Biology, Social Sciences, Natural Science, Pattern Recognition, Statistics, Data Mining, Economics and Business. If you are looking for reference about a cluster analysis, please feel free to browse our site for we have available Analysis Examples in word. So there are two main types in clustering that is considered in many fields, the Hierarchical Clustering Algorithm and the Partitional Clustering Algorithm.
- Hierarchical Clustering is a nested clustering that explains the algorithm and set of instructions by describing which creates dendrogram results. In some other ways, Hierarchical Clustering is the method of classifying groups that are organized as a tree. This method involves a process of looking for the pairs of samples that are similar to each other. Hierarchical Clustering also involves two algorithms mainly agglomerative algorithm and divisive algorithm.
– Agglomerative algorithm involves emphasizing individual clusters and eventually merge them with the closest pair of clusters.
– Divisive Algorithm includes all inclusive clusters and split them until only one cluster remains.
- Partitional Clustering is the dividing or decomposing of data in disjoint clusters. This type of clustering creates partition of the data that represents each cluster.
Clustering is mainly a very important method in determining the status of a business business. Data analysis such as Needs Analysis is and Risk Analysis are one of the most important methods that would help in determining.
The Importance Of Clustering
Why do we need Cluster Analysis? Cluster Analysis is very important because it serves as the determiner of the data unto which group is meaningful and which group is the useful one or which group is both. It has been said that clustering is either useful for understanding or for utility.
- For Understanding- one of the main goal of clustering or grouping sets of data or objects is to help human understand certain information presented. Since understanding is already a skill in a human’s system, clustering is already a huge help for clear and concise information needed in determining especially in business analysis. This helps determine the areas that needs to be improved, maintained or omitted.
- For Utility- Clustering is very helpful in terms of utility for it provides the individual data’s abstraction to those clusters that already reside. So the main concept of clustering for utility is determining the most representative of all prototypes.
Clustering is also very useful in terms of :
- Biology- Scientists and biologist has been using this method of classifying the hierarchical classification of living things
- Climate- This is very vital in helping scientists and geologists in understanding the Earth’s climate. Clustering has been very useful in chacking the pattern of atmospheric pressure and other activities of the earth
- Psychology- In understanding the human mind and behavior, clustering takes the vital role in determining and categorizing variations and subcategories.
- Information- The world is in need of information that supports also the day to day needs of information especially for students, doctors, scientists, everyone gets to check the world wide web, by that information in the internet has been sort out and categorized as well.
- So why is it really very important to use cluster analysis? Mainly because it has been part of our day to day lives, we can’t deny that it is also contributes a part of what we have in the world today. Other related topics you might want to check in our site that provides examples includes:
- Risk Analysis Examples
Needs Analysis Examples
Risk Management Examples