Data mining is a huge industry that intrudes in the lives of society by gathering information on individuals legally but without knowledge or consent.
With recent technical advances in processing power, storage capacity, and inter-connectivity of computer technology, Computer science data mining essay mining is seen as an increasingly important tool by modern business to transform unprecedented quantities of digital data into business intelligence giving an informational advantage.
It is currently used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. The growing consensus that data mining can bring real value has led to an explosion in demand for novel data mining technologies. Used to remove noise and inconsistent data.
It is used where the multiple data sources may be combined. IN this the data relevant to the analysis task are retrieved. It is where the data are transformed or consolidated into forms appropriate for mining by performing summery and aggregate operation.
It is essential process where intelligent methods are applied in order to extract data patterns. It is to identify the truly interesting patterns representing knowledge based on some interestingness measures.
It is where visualization and knowledge representation techniques are used to present the mined knowledge to the user. It is of interest to researchers in machine learning, pattern recognition, databases, statistics, artificial intelligence, knowledge achievement for expert systems, and data revelation.
The unifying goal of the KDD process is to extract knowledge from data in the context of large database. It does this by using data mining methods algorithms to extract identify what is deemed knowledge, according to the specifications of measures and thresholds, using a database along with any required preprocessing, sub sampling, and transformations of that database Data mining Model Techniques of data mining There are several major data mining techniques have been developed and used in data mining projects recently including association, classification, clustering, regression,prediction and sequential patterns.
Association Searche for relationship between variables. For example a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes.
This is sometimes called as market basket analysis. Classification Classification is the task of generalizing known structure to apply to new data. For example, an email program might attempt to classify an email as legitimate or spam. Common algorithms include decision tree learning, nearest neighbor, neural networks and support vector machines.
Clustering Clustering is the assignment of a set of observations into subsets so that observations in the same cluster are similar in some sense. Clustering is a method of unsupervised learningand a common technique for statistical data analysis used in many fieldsincluding machine learningdata mining, pattern recognition, image analysis, information retrieval and bioinformatics.
Regression Regression is a data mining function that predicts a number, Profit, saleshouse value, square footage, temperature, or distance could all be predicted using regression technique.
For example, a regression model could be used to predict the value of house based on location, number of rooms, lot size, and other factor. Regression models are tested by computing various statistics that measure the difference between the predicted and the expected values.
The historical data for a regression project a typically divided into two data sets: A regression models the past relationship between variables to predict their future behavior.
When one independent variable is used in a regression, it is called a simple regression 2. Sequential Pattern Sequence analysis is concerned with a subsequent purchase of a product or products given a previous buy.
For instance, buying an extended warranty is more likely to follow the purchase of TV or other electric appliances. There is a wide range of applications for sequence analysis in many areas of industry including customer shopping patterns, phone call patterns and web log streams.
Management Information System MIS is a system that provides information needed to manage organizations effectively. Management information system are regarded to be subset of the overall internal controls procedures in a business ,which cover the application of people, documents, technologies and procedures used by management accountants to solve business problems such as costing the productservice or a business- wide strategy.
For example, if students attend a technical college in hopes to be an engineer they will focus on engineering only. A degree, diploma or certificate in a technical major will give you a special skill or practical knowledge in a particular field such as engineering, health and medicine, computers and a lot of other technically oriented fields.
The Technical College System was designed in to help prepare people for the kind of jobs that companies need employees for. In other words, they offer programs that will help you get a job Career. In the 21st century, the rate of change in social and technical systems is accelerating, and the mechanization of society and work requires that all Individuals reach new levels of educational accomplishment.
Career and Technical Education is defined as providing a context for learning and applying educational skills. Education systems in developing countries struggle with many issues like grade repetition, leaving colleges, teacher absenteeism, and less learning than the prospectus standards suggest.
A good education system is important in the advancement of a developing country Education systems in developing countries face the similar issues of inefficient budgets, the building of unnecessary non technical colleges, paying inadequate teachers, and buying colleges the predicted academic Performance of students in technical is higher than students attending non technical colleges.
Poor households who may struggle to afford non technical consider many factors such as less fees, proximity, and quality. Despite the cost of technical education poor families value the high quality education that this provides to students and strive to afford this opportunity but in less fess.
Non technical colleges in developing countries face the issue of teacher absenteeism.Data excavation is what tech industry is acquiring into. Companies have one million millions of informations points and looking for a agency to change over it into gross.
Data Mining In The Technology Sector Computer Science Essay. Home / Free Essays / Data excavation is what tech industry is acquiring into. Companies have one million. Data mining is an analytic process of exploring huge amount of data, extract useful information, finding consistent patterns and trends between variables, and build predictive computer models from the relationship discovered using a combination of classical statistics, machine learning and.
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