BCA
... Realism, 3D Geometric tranformations, Reflection with Respect to Given Plane, Reflection with Respect to Any Plane 3D Display Methods - Three Dimensional Viewing, Viewing Parameters, Transformation from World coordinate to , Viewing co-ordinates, Projections, 3D Clipping, 3D Midpoint Subdivision Alg ...
... Realism, 3D Geometric tranformations, Reflection with Respect to Given Plane, Reflection with Respect to Any Plane 3D Display Methods - Three Dimensional Viewing, Viewing Parameters, Transformation from World coordinate to , Viewing co-ordinates, Projections, 3D Clipping, 3D Midpoint Subdivision Alg ...
Dr Sherif Kamel
... The goal of GDSS is to improve the productivity of decision-making meetings, either by speeding up the decision-making process or by improving the quality of the resulting decisions, or both ...
... The goal of GDSS is to improve the productivity of decision-making meetings, either by speeding up the decision-making process or by improving the quality of the resulting decisions, or both ...
Intrusion Detection Using Data Mining Along Fuzzy Logic and
... of S leaves no room for belief in the attribute S. Plausibility also ranges from 0 to 1. The belief – Plausibility interval measures not only the level of belief in some propositions but also the amount of information it has. The work on be fuzzy logic based reasoning can be replaced by Dempster -Sh ...
... of S leaves no room for belief in the attribute S. Plausibility also ranges from 0 to 1. The belief – Plausibility interval measures not only the level of belief in some propositions but also the amount of information it has. The work on be fuzzy logic based reasoning can be replaced by Dempster -Sh ...
- NEO Network
... expertise by elevating the consistency and objectivity of decision making across an organization ...
... expertise by elevating the consistency and objectivity of decision making across an organization ...
Chapter8
... Replace attribute value by difference (residual) between the attribute's value and the prediction of that attribute from a simple regression based on the previous PLS direction Compute the dot product between each attribute's residual vector and the class vector in turn, this yields the coefficients ...
... Replace attribute value by difference (residual) between the attribute's value and the prediction of that attribute from a simple regression based on the previous PLS direction Compute the dot product between each attribute's residual vector and the class vector in turn, this yields the coefficients ...
An Efficient Approach to the Clustering of Large Data Sets Using P
... We introduce a lazy classifier that does not require a training phase. Data that is no longer considered accurate can be eliminated or replaced without the need to recreate a classifier or redo an optimization procedure. Our classifier improves on the accuracy of the Naive Bayesian classifier by tre ...
... We introduce a lazy classifier that does not require a training phase. Data that is no longer considered accurate can be eliminated or replaced without the need to recreate a classifier or redo an optimization procedure. Our classifier improves on the accuracy of the Naive Bayesian classifier by tre ...
IARIW_Tokio1996_LandAccount_Parker_Steurer_Uhel_Weber
... process (the driving forces). Artificialisation can be due to economic activities such as manufacturing and mining, agriculture, construction and public works, tourism, transport... An opposite process can take place, for example in the case of abandoning of land by agriculture. These activities are ...
... process (the driving forces). Artificialisation can be due to economic activities such as manufacturing and mining, agriculture, construction and public works, tourism, transport... An opposite process can take place, for example in the case of abandoning of land by agriculture. These activities are ...
Deep learning using genetic algorithms
... be trained in reasonable time. Once trained, the networks are relatively rigid, being able to be applied only to the exact problem domain they are trained against. A network designed to identify three different species of cat in images, for instance, could not be used to find if an image did not con ...
... be trained in reasonable time. Once trained, the networks are relatively rigid, being able to be applied only to the exact problem domain they are trained against. A network designed to identify three different species of cat in images, for instance, could not be used to find if an image did not con ...
number of pages referred in a session (Session time=30 minutes)
... potential users, but had the drawback that it completely ignored the entries made by network robots. Search engines normally use network robots to crawl through the web pages to collect information. The number of records created by these robots in a log file is extremely high and has a negative impa ...
... potential users, but had the drawback that it completely ignored the entries made by network robots. Search engines normally use network robots to crawl through the web pages to collect information. The number of records created by these robots in a log file is extremely high and has a negative impa ...
A GIS-BASED VISUALIZATION MODULE FOR
... variables. Information visualization is essential to the understanding of large highdimensional datasets. However, it is difficult to perceive high-dimensional visualizations and therefore dimensionality reduction is required. The challenge then is in utilizing a model that effectively reduces the d ...
... variables. Information visualization is essential to the understanding of large highdimensional datasets. However, it is difficult to perceive high-dimensional visualizations and therefore dimensionality reduction is required. The challenge then is in utilizing a model that effectively reduces the d ...
Michel Ballings
... • Michel Ballings. Social Media Analytics. Seminar Talk. The University of Tennessee, Haslam College of Business, Department of Management, November 4, 2014 • Michel Ballings. Advances in Social Media Analytics. Seminar Talk. The University of Tennessee, College of Engineering, Department of Industr ...
... • Michel Ballings. Social Media Analytics. Seminar Talk. The University of Tennessee, Haslam College of Business, Department of Management, November 4, 2014 • Michel Ballings. Advances in Social Media Analytics. Seminar Talk. The University of Tennessee, College of Engineering, Department of Industr ...
A Sentiment Analysis as a Tool to Identify The Status Of Universities
... The input of this stage is inherited from text mining results. In this research ITU is considered as a product and the features are defined as education, campus and corporate reputation. An empirical study on sentiment categorization on ITU is conducted. Both statistical and rule based models are de ...
... The input of this stage is inherited from text mining results. In this research ITU is considered as a product and the features are defined as education, campus and corporate reputation. An empirical study on sentiment categorization on ITU is conducted. Both statistical and rule based models are de ...
Machine Learning in Computer Vision – Tutorial
... • Affects the convergence of any learning algorithm. • In some applications, we know that there are only a few variables, for e.g., face pose and illumination. • Data lie on some low-dimensional subspace/manifold in the high-dimensional space. ...
... • Affects the convergence of any learning algorithm. • In some applications, we know that there are only a few variables, for e.g., face pose and illumination. • Data lie on some low-dimensional subspace/manifold in the high-dimensional space. ...
Machine Learning in Computer Vision – Tutorial
... • Affects the convergence of any learning algorithm. • In some applications, we know that there are only a few variables, for e.g., face pose and illumination. • Data lie on some low-dimensional subspace/manifold in the high-dimensional space. ...
... • Affects the convergence of any learning algorithm. • In some applications, we know that there are only a few variables, for e.g., face pose and illumination. • Data lie on some low-dimensional subspace/manifold in the high-dimensional space. ...
computational intelligence and visualisation
... sequence of iterations of finding a new x location. Each of the iterations updates the old xvalue as follows: ...
... sequence of iterations of finding a new x location. Each of the iterations updates the old xvalue as follows: ...
A Novel Metaheuristic Data Mining Algorithm for the Detection and
... with an aim to assist the experts for making a diagnosis over PD. The research dataset comprises of so many voice signals obtained from 31 people (23 with people having PD and 8 healthier ones). Thus, this study relied on PD data to set obtained from University of California (UCI) machine learning d ...
... with an aim to assist the experts for making a diagnosis over PD. The research dataset comprises of so many voice signals obtained from 31 people (23 with people having PD and 8 healthier ones). Thus, this study relied on PD data to set obtained from University of California (UCI) machine learning d ...
INTELLIGENT TELECOMMUNICATION TECHNOLOGIES
... success. In the field of telecommunications, this is because it is often too difficult to specify a behavioral or functional model at a sufficiently high level to make the model practical and yet have it be useful. The design of telecommunication expert systems needs to recognize that virtually all ...
... success. In the field of telecommunications, this is because it is often too difficult to specify a behavioral or functional model at a sufficiently high level to make the model practical and yet have it be useful. The design of telecommunication expert systems needs to recognize that virtually all ...
Simple Algorithmic Theory of Subjective Beauty, Novelty
... the essential ideas in previous publications on this topic 34)∼38), 44), 47), 51), 54), 60), 61), 72) . Formal details are left to the Appendices of previous papers, e.g., 54), 60) . As discussed in the next section, the principles at least qualitatively explain many aspects of intelligent agents su ...
... the essential ideas in previous publications on this topic 34)∼38), 44), 47), 51), 54), 60), 61), 72) . Formal details are left to the Appendices of previous papers, e.g., 54), 60) . As discussed in the next section, the principles at least qualitatively explain many aspects of intelligent agents su ...
DeepMetabolism: A Deep Learning System To Predict
... accuracy for predictions, with PCC reaching only 0.39~0.67 and matched predictions reaching only 16.7~50.0%. The time cost also increased from 28.3 min to 102.7 min. The increased solution time was due to the large solution space and the lack of “warm start” initial guesses of parameters. Consequent ...
... accuracy for predictions, with PCC reaching only 0.39~0.67 and matched predictions reaching only 16.7~50.0%. The time cost also increased from 28.3 min to 102.7 min. The increased solution time was due to the large solution space and the lack of “warm start” initial guesses of parameters. Consequent ...
Relational Topographic Maps - Institut für Informatik, TU Clausthal
... Median clustering has the benefit that it builds directly on the derivation of SOM and NG from a cost function. Thus, the resulting algorithms share the simplicity of batch NG and SOM, its mathematical background and convergence, as well as the flexibility to model additional information by means of ...
... Median clustering has the benefit that it builds directly on the derivation of SOM and NG from a cost function. Thus, the resulting algorithms share the simplicity of batch NG and SOM, its mathematical background and convergence, as well as the flexibility to model additional information by means of ...
BIIIG : Enabling Business Intelligence with Integrated Instance Graphs
... to which subsets of the data sources need to be mapped. We follow a bottom-up approach for data integration that preserves the sources metadata as well as instance data and relationships but integrate them into uniform graph models. At the metadata level, we describe sources in terms of classes and ...
... to which subsets of the data sources need to be mapped. We follow a bottom-up approach for data integration that preserves the sources metadata as well as instance data and relationships but integrate them into uniform graph models. At the metadata level, we describe sources in terms of classes and ...
Ontology-based semantic annotation: an automatic hybrid rule
... works well on the majority of concepts, but produces poor results for some concepts. To overcome this limitation, we have adopted a strategy consisting in filtering (deleting) rules that produce lots of erroneous matches. More precisely, we have deleted rules that match at least one time and that co ...
... works well on the majority of concepts, but produces poor results for some concepts. To overcome this limitation, we have adopted a strategy consisting in filtering (deleting) rules that produce lots of erroneous matches. More precisely, we have deleted rules that match at least one time and that co ...
The Road to Enterprise AI
... Wisely, Gartner’s predictions go out only three years. On 25-Jan, 2017, sixty eight years after it was published, George Orwell’s dystopian 1984 became the number one best-selling book on Amazon. Orwell’s Big Brother, omnipresent government surveillance, Ministry of Truth that dispenses lies or “alt ...
... Wisely, Gartner’s predictions go out only three years. On 25-Jan, 2017, sixty eight years after it was published, George Orwell’s dystopian 1984 became the number one best-selling book on Amazon. Orwell’s Big Brother, omnipresent government surveillance, Ministry of Truth that dispenses lies or “alt ...
Correlation-based Attribute Selection using Genetic Algorithm
... class concept but is not redundant to any of the other relevant features. If we adopt the correlation between two variables as a goodness measure, the above definition becomes that a feature is good if it is highly correlated to the class but not highly correlated to any of the other features. In ot ...
... class concept but is not redundant to any of the other relevant features. If we adopt the correlation between two variables as a goodness measure, the above definition becomes that a feature is good if it is highly correlated to the class but not highly correlated to any of the other features. In ot ...
“Genetic Algorithm as an Attribute Subset Selection tool during
... class concept but is not redundant to any of the other relevant features. If we adopt the correlation between two variables as a goodness measure, the above definition becomes that a feature is good if it is highly correlated to the class but not highly correlated to any of the other features. In ot ...
... class concept but is not redundant to any of the other relevant features. If we adopt the correlation between two variables as a goodness measure, the above definition becomes that a feature is good if it is highly correlated to the class but not highly correlated to any of the other features. In ot ...