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Machine learning is an application of Artificial Intelligence that supports an architecture with the capability to learn and enhance from experience without being definitely programmed automatically.It can be used by search engines including Google and Bing to rank internet pages or to determine which advertisement to display to which user. It can be used by social networks including Facebook and Instagram to make a custom feed for each user or to tag the customer by the images that was uploaded.The classification of machine learning is as follows −Supervised Learning − Supervised learning is a type of machine learning method in ... Read More
There are various applications of machine learning which are as follows −Social media services − Machine learning is an essential role in personalizing news feed to superior advertisement focusing over social media. Facebook needs machine learning to display news feed to the user based on its interests by treating items clicked earlier by that user.Facebook always takes note of the friends that it can linked with, the profiles that it can visit, interests, workplace, and on the basis of this continuous learning, a file of Facebook users are suggested for us to become friends with.The Face Recognition nature of Facebook ... Read More
It is a statistical approach for preprocessing data to filter out irrelevant attributes or rank the relevant attribute. Measures of attribute relevance analysis can be used to recognize irrelevant attributes that can be unauthorized from the concept description process. The incorporation of this preprocessing step into class characterization or comparison is defined as an analytical characterization.Data discrimination makes discrimination rules which are a comparison of the general features of objects between two classes defined as the target class and the contrasting class.It is a comparison of the general characteristics of targeting class data objects with the general characteristics of objects ... Read More
Class discrimination is defined as classism. It is prejudice or discrimination based on social class. It involves individual attitudes, behaviors, systems of policies, and practices that are set up to benefit the upper class at the amount as the lower class.Classism can define personal prejudice against lower classes and institutional classism, just as the term racism can define either strictly to personal prejudice or institutional racism. The latter has been represented as how conscious or unconscious classism is clear in the several institutions of our society".Class discrimination can be viewed in several forms of media including television shows, films, and ... Read More
Machine learning is an application of Artificial Intelligence that supports an architecture with the capability to learn and enhance from experience without being definitely programmed automatically.It can be used by search engines including Google and Bing to rank internet pages or to determine which advertisement to display to which user. It can be used by social networks including Facebook and Instagram to make a custom feed for each user or to tag the customer by the images that was uploaded.It can be used by banks to identify whether an online transaction is fraudulent and by e-commerce websites including Amazon and ... Read More
Data generalization summarizes data by replacing relatively low-level values (including numeric value for attribute age) with high-level concepts (including young, middle-aged, and senior). Therefore, it is a process that abstracts a huge set of task-relevant information in a database from a relatively low conceptual level to higher conceptual levels.Following are the two approaches for the efficient and flexible generalization of large data sets −OLAP approach − The data cube technology can be treated as a data warehouse-based, pre-computation-oriented, materialized view approach. It implements offline aggregation earlier an OLAP or data mining query is moved for processing.Attribute-oriented induction approach − It ... Read More
Agglomerative clustering is a bottom-up clustering method where clusters have subclusters, which in turn have sub-clusters, etc. It can start by placing each object in its cluster and then mix these atomic clusters into higher and higher clusters until all the objects are in an individual cluster or until it needs definite termination condition. Some hierarchical clustering methods used to this type. The distinct only in their description of between-cluster similarity.For example, a method called AGNES (Agglomerative Nesting), need the single-link techniques and operates as follows. Consider there are group of objects placed in a rectangle. Initially, every object is ... Read More
Association rule learning is a type of unsupervised learning methods that tests for the dependence of one data element on another data element and create appropriately so that it can be more effective. It tries to discover some interesting relations or relations among the variables of the dataset. It depends on several rules to find interesting relations between variables in the database.The association rule learning is the important technique of machine learning, and it is employed in Market Basket analysis, Web usage mining, continuous production, etc. In market basket analysis, it is adequate used by several big retailers to find ... Read More
Concept DescriptionConcept Description is a definitive type of data mining. It defines a set of data including frequent buyers, graduate candidates, etc. It describes the characterization and comparison of the data. It is also known as a class description when the concept to be described is defined as a class of objects. These descriptions can be determined with the support of data characterization.Data characterization is a summarization of the general characteristics of the target class of data. The data relating to a specific user-defined class is usually recovered by a database query. The output of data characterization can be presented ... Read More
Market basket analysis does not represent an individual method and it represents a set of business issues related to understanding point-of-sale transaction data. Market basket data is transaction data that represents three fundamentally different entities such as users, orders (also called purchases or baskets or, in academic papers, item sets) and Items.The order is the component data structure for market basket data. An order describe a single purchase event by a user. This can correlate to a user ordering several products on a website or to users buying a basket of groceries or to a user buying a several items ... Read More