Clustering in daily life

Cluster Analysis is finding groups of objects such that the object in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups.
It's finding similarities between data according to the characteristics found in the data and grouping similar data objects into clusters.


I found examples of clustering analysis in daily life:
  • Marketing : It helps the marketers discover distinct groups in their customer bases, and then use this knowledge to develop targeted marketing programs.
  • Land use : It identification of areas of similar land use in an earth observation database.
  • Insurance : It identifying groups of houses according to their house type, value, and geographical location
  • Earth-quake studies : Observed earthquake epicenters should be clustered along continent faults


Comments

Post a Comment

Popular posts from this blog

Quantification in Social Network

Quantification is closely related to classification : however, the goal of classification is different, since in classification we are interested in correctly guessing the true class label of each single individual. Instead, in quantification we are interested in classifying our individuals with the goal of estimating the class prevalence where is not strictly necessary to classify correctly each single individual. Classification and quantification are different because, a perfect classifier is also a perfect quantifier, not necessarily a good classifier is also good quantifier. Quantification aims at finding the class frequencies in a set of unlabeled data, while classification aims at determining the class of each specific item in the same dataset. In other words, a quantifier does not care about perfectly predicting the class of a single item, but to guess the global trend of the classes in a new set of data.
Read more

Artificial Intelligence

Image
According to Quartz says that "Artificial Intelligence is software or a computer program with a mechanism to learn. It then uses that knowledge to make a decision in a new situation, as humans do. The researchers building this software try to write code that can read images, text, video, or audio, and learn something from it. Once a machine has learned, that knowledge can be put to use elsewhere", means that the AI powered machines don't need to take breaks or rest and they can analyze massive volumes of information all at once. AI based technologies are already being used to help human benefit from significant improvements and increased efficiency in nearly every area of life. Artificial Intelligence is able to see, hear and comprehend. means that it can see the computer vision, hear speech recognition and understand the natural language processing more than ever before. Because this was once a uniquely human characteristics, AI will open up a whole new worl...
Read more

Text Mining (Sentiment Analysis, Topic Modelling, Word Cloud)

Image
I would like to do Text Mining Analysis by using Orange 3 to know the Sentiment Analysis, Topic Modelling and Word Cloud. The picture above is the layout of Orange 3 when we want to do the analysis, I was connected to Twitter to get the API's key and API's key secret. The topic that I choose is discussed about #Seungri Bigbang that now is involved in the case of prostitution, and I took 100 samples of tweets. Sentiment Analysis We can see that there are 4 sentiments, which are fear, joy, sadness, and surprise. Related to the topic, there are so many people or Seungri's fans got surprised about his case that he involved in prostitution. Then, we can see that sadness and fear by his fans comes up because it is happens to Seungri Bigbang. Sentiment Analysis is used to explain how sentiment the user of Twitter about the topics, it also the emotion that related with an individual. Topic Modelling In topic modelling, we can see that there are 10 keyw...
Read more