Feature Selection with Linked Data in Social Media
... are followed by the same user, their posts are similar in topics. For example, in Figure 2(c), both users u2 and u4 are followed by user u1 and then their posts {p3 , p4 , p5 } and {p8 } are of more similar topics. It is similar to the co-citation relation [18] in citation analysis: if two papers ar ...
... are followed by the same user, their posts are similar in topics. For example, in Figure 2(c), both users u2 and u4 are followed by user u1 and then their posts {p3 , p4 , p5 } and {p8 } are of more similar topics. It is similar to the co-citation relation [18] in citation analysis: if two papers ar ...
Getting Unique Solution in Data Exchange
... The problem of data exchange was formally defined in [10] as the problem of transforming data structured under a source schema into data structured under a target schema w.r.t a mapping consisting of dependencies. The main task of data exchange is materializing a valid target instance (called a solu ...
... The problem of data exchange was formally defined in [10] as the problem of transforming data structured under a source schema into data structured under a target schema w.r.t a mapping consisting of dependencies. The main task of data exchange is materializing a valid target instance (called a solu ...
Neural Network Applications in Stock Market Predictions
... As illustrated in the Table 2, the researchers have used various data models, and no model can be considered as the predominant. This variety could cause the difficulties in constructing a paradigm of NN efficiency. The number of input variables ranges from 3 [9] to 88 [4]. However, majority of vari ...
... As illustrated in the Table 2, the researchers have used various data models, and no model can be considered as the predominant. This variety could cause the difficulties in constructing a paradigm of NN efficiency. The number of input variables ranges from 3 [9] to 88 [4]. However, majority of vari ...
1993 - KDnuggets
... methods, Fayyad and his colleagues were able to recognize objects at least one magnitude fainter in resolution than was previously possible and achieve an accuracy of about 94 percent. This work is noteworthy as a real application of machine learning to a difficult problem with results that are bein ...
... methods, Fayyad and his colleagues were able to recognize objects at least one magnitude fainter in resolution than was previously possible and achieve an accuracy of about 94 percent. This work is noteworthy as a real application of machine learning to a difficult problem with results that are bein ...
Human Talent Prediction in HRM using C4.5 Classification Algorithm
... D. Decision Tree Techniques Decision tree can produce a model with rules that are human-readable and interpretable. The classification task using decision tree technique can be performed without complicated computations and the technique can be used for both continuous and categorical variables. Thi ...
... D. Decision Tree Techniques Decision tree can produce a model with rules that are human-readable and interpretable. The classification task using decision tree technique can be performed without complicated computations and the technique can be used for both continuous and categorical variables. Thi ...
Machine Humanity: How the Machine Learning of Today is
... use cases. And we can think beyond the realm of what was possible just a few years ago. Organizations that invest in know-how, gain experience, and approach machine learning pragmatically today will be ready as the technology continues to advance and new opportunities arise. Organizations that don’t ...
... use cases. And we can think beyond the realm of what was possible just a few years ago. Organizations that invest in know-how, gain experience, and approach machine learning pragmatically today will be ready as the technology continues to advance and new opportunities arise. Organizations that don’t ...
Learning from Heterogeneous Sources via
... vector-based features and the relational features simultaneously. Second and foremost, most of the previous works require the data sources to have records of all instances in order to enable the mapping, while the proposed GBC model does not have this constraint. Another area of related work is coll ...
... vector-based features and the relational features simultaneously. Second and foremost, most of the previous works require the data sources to have records of all instances in order to enable the mapping, while the proposed GBC model does not have this constraint. Another area of related work is coll ...
Intelligent Techniques in Decision Making: A Survey
... Keywords: Artificial Intelligence, Decision Support System, Fuzzy System, Intelligent Techniques, Neural Network, Rough Set ...
... Keywords: Artificial Intelligence, Decision Support System, Fuzzy System, Intelligent Techniques, Neural Network, Rough Set ...
A Machine Learning Approach for Abstraction based on the Idea of
... data. Besides conventional, statistical functions as correlation and regression, methods from signal theory, pattern recognition, clustering, computational neuroscience, fuzzy systems, evolutionary algorithms, swarm intelligence and machine learning are applied [3]. Especially computationally intell ...
... data. Besides conventional, statistical functions as correlation and regression, methods from signal theory, pattern recognition, clustering, computational neuroscience, fuzzy systems, evolutionary algorithms, swarm intelligence and machine learning are applied [3]. Especially computationally intell ...
C++ Programming: Program Design Including Data Structures
... C++ Programming: Program Design Including Data Structures C++ Programming: Program Design Including Data Structures, 6th Edition Programming #8:C Programming Success in a Day & Android Programming In a Day! (C Programming, C++programming, C++ programming language, Android , Android Programming, Andr ...
... C++ Programming: Program Design Including Data Structures C++ Programming: Program Design Including Data Structures, 6th Edition Programming #8:C Programming Success in a Day & Android Programming In a Day! (C Programming, C++programming, C++ programming language, Android , Android Programming, Andr ...
Computing Information Gain in Data Streams
... domain(s) of the data values is discrete, either nominal or consisting of a few numerical values. In discrete domains, the data can be represented by simply counting the number of instances of each value. Often this simple representation is sufficient and the memory usage much less than the actual s ...
... domain(s) of the data values is discrete, either nominal or consisting of a few numerical values. In discrete domains, the data can be represented by simply counting the number of instances of each value. Often this simple representation is sufficient and the memory usage much less than the actual s ...
Extending Data Processing Capabilities of Relational Database
... Decomposing the three main components of a Jelly View : External Matching, Internal Matching and Logic Program, is a crucial problem. They must comply with the relational model. One possible approach is illustrated in the ER diagram in Fig. 1. External Matching matches a relation name and a clause n ...
... Decomposing the three main components of a Jelly View : External Matching, Internal Matching and Logic Program, is a crucial problem. They must comply with the relational model. One possible approach is illustrated in the ER diagram in Fig. 1. External Matching matches a relation name and a clause n ...
Table 1 shows the statistics based on all questions answered,... some students answered four questions. Averages are fairly consistent across
... Some possibilities include: Creativity and imagination are currently not well understood, and are thus, difficult to describe in an executable computer model. An ability to recognise faces and differentiate between male and female faces is another area where clear rules are difficult to elicit becau ...
... Some possibilities include: Creativity and imagination are currently not well understood, and are thus, difficult to describe in an executable computer model. An ability to recognise faces and differentiate between male and female faces is another area where clear rules are difficult to elicit becau ...
Ordering attributes for missing values prediction and
... introduced some and performed the classification again to analyze the results. Missing values were randomly [18] introduced in the attributes 1, 2, 3 and 4 (Sepal length, Sepal width, Petal length and Petal width) separately. Three new samples were generated for each one of the attributes, the f~st ...
... introduced some and performed the classification again to analyze the results. Missing values were randomly [18] introduced in the attributes 1, 2, 3 and 4 (Sepal length, Sepal width, Petal length and Petal width) separately. Three new samples were generated for each one of the attributes, the f~st ...
Introduction to Database Systems
... The sheer and often mind-boggling quantity of decision support data is likely to require the latest hardware and software. It is also imperative to have very detailed procedures to orchestrate the flow of data from the operational databases to the Dare Warehouse. To implement and support the Data Wa ...
... The sheer and often mind-boggling quantity of decision support data is likely to require the latest hardware and software. It is also imperative to have very detailed procedures to orchestrate the flow of data from the operational databases to the Dare Warehouse. To implement and support the Data Wa ...
Classifier Ensembles for Detecting Concept Change in Streaming
... • Instances versus batches of data. Streaming instances of data can be converted into streaming batches or “chunks” of data. The reverse is also possible but batch data usually comes in massive quantities, and instance-based processing may be too timeconsuming. • Explicit versus implicit change dete ...
... • Instances versus batches of data. Streaming instances of data can be converted into streaming batches or “chunks” of data. The reverse is also possible but batch data usually comes in massive quantities, and instance-based processing may be too timeconsuming. • Explicit versus implicit change dete ...
Intelligent Support for Exploratory Data Analysis
... Automated strategic reasoning could provide enormous benefits, greatly reducing the work load of statisticians and giving nonstatisticians easy access to expert advice. Over the past 15 years researchers have developed strategies for regression analysis (Gale 1986), regression-based data description ...
... Automated strategic reasoning could provide enormous benefits, greatly reducing the work load of statisticians and giving nonstatisticians easy access to expert advice. Over the past 15 years researchers have developed strategies for regression analysis (Gale 1986), regression-based data description ...
Revision Resources File
... Robotics involves devices which are programmed to do things by giving them a set of instructions. Bionics is often used alongside robotics. This is where nature is used when designing modern technology. Robotics arms can be built, for example, by trying to copy the muscles which make human arms work ...
... Robotics involves devices which are programmed to do things by giving them a set of instructions. Bionics is often used alongside robotics. This is where nature is used when designing modern technology. Robotics arms can be built, for example, by trying to copy the muscles which make human arms work ...
Constraint Mining in Business Intelligence: A Case Study of
... Business intelligence (BI) is a broad term normally used to refer to any aspect of computer-based business applications including decision support, information management, marketing automation, and intelligent data analysis [5, 10, 14]. The task of automatically extracting patterns from data related ...
... Business intelligence (BI) is a broad term normally used to refer to any aspect of computer-based business applications including decision support, information management, marketing automation, and intelligent data analysis [5, 10, 14]. The task of automatically extracting patterns from data related ...
THE BRITISH COMPUTER SOCIETY KNOWLEDGE BASED SYSTEMS THE BCS PROFESSIONAL EXAMINATIONS
... relevant to adaptive computing. [4.1, 4.2, 4.3, 4.4] 6. The learner will know the major AI application areas and understand the AI techniques used within them. [6.1, 6.2, 6.3, 6.5, 6.6, 6.7] 7. The learner will know how AI technology has been used in real situations particularly on the Internet. [7. ...
... relevant to adaptive computing. [4.1, 4.2, 4.3, 4.4] 6. The learner will know the major AI application areas and understand the AI techniques used within them. [6.1, 6.2, 6.3, 6.5, 6.6, 6.7] 7. The learner will know how AI technology has been used in real situations particularly on the Internet. [7. ...
Application of Musical Information Retrieval (MIR)
... shows an example of seismic data where the different gas-bearing channels have been drilled. They are here labeled, respectively, as Channel “A”, “C” and “D”. There is another channel labelled “Channel B” not included in this figure. Our taxonomy represents just an initial hypothesis that can be imp ...
... shows an example of seismic data where the different gas-bearing channels have been drilled. They are here labeled, respectively, as Channel “A”, “C” and “D”. There is another channel labelled “Channel B” not included in this figure. Our taxonomy represents just an initial hypothesis that can be imp ...
Table 4.2 The sample memberships and kernel set
... By the decision rule, the RRI of this patient will be identified into the learned dead pattern of RRI. (3) Similarly, for new sample (II), the observations which belongs to the sample kernel set with respect to total observations is 0.034(=17/500), which is smaller than 0.05. By the radius of sample ...
... By the decision rule, the RRI of this patient will be identified into the learned dead pattern of RRI. (3) Similarly, for new sample (II), the observations which belongs to the sample kernel set with respect to total observations is 0.034(=17/500), which is smaller than 0.05. By the radius of sample ...
CLASSIFICATION AND CLUSTERING MEDICAL DATASETS BY
... processes information. Artificial neural networks are collections of mathematical models that represent some of the observed properties of biological nervous systems and draw on the analogies of adaptive biological learning. The key element of ANN is topology. The ANN consists of a large number of h ...
... processes information. Artificial neural networks are collections of mathematical models that represent some of the observed properties of biological nervous systems and draw on the analogies of adaptive biological learning. The key element of ANN is topology. The ANN consists of a large number of h ...
PMCRI: A Parallel Modular Classification Rule
... using PrismTCS or any other algorithm that generates a model from data: (1) the volume of data (number of instances and attributes) (2) the attribute types (continuous attributes generally take much longer to process than categorical ones) (3) the complexity of the model produced in the chosen repre ...
... using PrismTCS or any other algorithm that generates a model from data: (1) the volume of data (number of instances and attributes) (2) the attribute types (continuous attributes generally take much longer to process than categorical ones) (3) the complexity of the model produced in the chosen repre ...