Data Clustering using Particle Swarm Optimization
... Hybrid PSO algorithm doing so for 4 of the 6 problems. It is also the PSO approaches that succeeded in forming the more compact clusters. The Hybrid PSO formed the most compact clusters for 4 problems, the standard PSO for 1 problem, and the K-means algorithm for 1 problem. The results above show a ...
... Hybrid PSO algorithm doing so for 4 of the 6 problems. It is also the PSO approaches that succeeded in forming the more compact clusters. The Hybrid PSO formed the most compact clusters for 4 problems, the standard PSO for 1 problem, and the K-means algorithm for 1 problem. The results above show a ...
Short Course III - David Kleinfeld - University of California San Diego
... and single electrode recordings, as well as more contemporary multielectrode recordings or imaging techniques. These quantitative methods have now reached a certain level of maturity, indicated by common measures and signal processing algorithms used in research papers, shared analysis software (suc ...
... and single electrode recordings, as well as more contemporary multielectrode recordings or imaging techniques. These quantitative methods have now reached a certain level of maturity, indicated by common measures and signal processing algorithms used in research papers, shared analysis software (suc ...
What is Decision Support? - Prof. Antonio Carlos M. Mattos
... Warehousing and OLAP, and Group Decision Support. The paper is concluded by presenting some other possible classifications of DS and discussing some recent trends of future DS development. 2 SURVEY In April 2001, we conducted an ad-hoc survey of WWW documents related to DS. We used the AltaVista Sea ...
... Warehousing and OLAP, and Group Decision Support. The paper is concluded by presenting some other possible classifications of DS and discussing some recent trends of future DS development. 2 SURVEY In April 2001, we conducted an ad-hoc survey of WWW documents related to DS. We used the AltaVista Sea ...
Strategies for Mining User Preferences in a Data - SEER-UFMG
... A data stream may be seen as a sequence of relational tuples that arrive continuously in variable time. Some typical fields of application for data streams are: financial market, web applications and sensor data. Traditional approaches for data mining cannot successfully process the data streams mai ...
... A data stream may be seen as a sequence of relational tuples that arrive continuously in variable time. Some typical fields of application for data streams are: financial market, web applications and sensor data. Traditional approaches for data mining cannot successfully process the data streams mai ...
Shrinking Number of Clusters by Multi-Dimensional Scaling
... in-depth analysis by laying up the documents with similar characteristics, not by accurately separating all the documents. Classification needs no more worrisome because the subjects to be classified are clear and the number of classifications is same as that of the subjects to be classified. Cluste ...
... in-depth analysis by laying up the documents with similar characteristics, not by accurately separating all the documents. Classification needs no more worrisome because the subjects to be classified are clear and the number of classifications is same as that of the subjects to be classified. Cluste ...
novel sequence representations Reliable prediction of T
... comparable performance. In the following we will use the Blosum50 matrix when we refer to Blosum sequence encoding. A last encoding scheme is defined in terms of a hidden Markov model. The details of this encoding are described later in section 3.3. The sparse versus the Blosum sequence-encoding sch ...
... comparable performance. In the following we will use the Blosum50 matrix when we refer to Blosum sequence encoding. A last encoding scheme is defined in terms of a hidden Markov model. The details of this encoding are described later in section 3.3. The sparse versus the Blosum sequence-encoding sch ...
A Review of Decision Support Systems for - CEUR
... Analysis (K-T), Analytical Hierarchy Process (AHP), MultiAttribute Utility Theory Analysis (MAUT) or Multi Criteria Decision Analysis (MCDA) [44, 56, 18, 52, 22]. However, ongoing research aims to find out which method is more appropriate for which type of problem, to differ between advantages and d ...
... Analysis (K-T), Analytical Hierarchy Process (AHP), MultiAttribute Utility Theory Analysis (MAUT) or Multi Criteria Decision Analysis (MCDA) [44, 56, 18, 52, 22]. However, ongoing research aims to find out which method is more appropriate for which type of problem, to differ between advantages and d ...
Robotic Process Automation
... Infosys Automation. We automated incident management by creating a workforce of intelligent robots who learn and resolve incidents and AI capabilities with self-learning and self-healing. ...
... Infosys Automation. We automated incident management by creating a workforce of intelligent robots who learn and resolve incidents and AI capabilities with self-learning and self-healing. ...
Reliable prediction of T-cell epitopes using neural networks with
... comparable performance. In the following we will use the Blosum50 matrix when we refer to Blosum sequence encoding. A last encoding scheme is defined in terms of a hidden Markov model. The details of this encoding are described later in section 3.3. The sparse versus the Blosum sequence-encoding sch ...
... comparable performance. In the following we will use the Blosum50 matrix when we refer to Blosum sequence encoding. A last encoding scheme is defined in terms of a hidden Markov model. The details of this encoding are described later in section 3.3. The sparse versus the Blosum sequence-encoding sch ...
Microarray Missing Values Imputation Methods
... neighbor (SKNN) method is a cluster-based method that uses the imputed missing values in a later imputation. SKNN method differs from traditional KNNimpute in that it imputes the missing values sequentially from the gene having the least missing values, and uses the imputed values for the subsequent ...
... neighbor (SKNN) method is a cluster-based method that uses the imputed missing values in a later imputation. SKNN method differs from traditional KNNimpute in that it imputes the missing values sequentially from the gene having the least missing values, and uses the imputed values for the subsequent ...
native rendition
... solutions and companies looking to implement AI. Drivers include a highly educated workforce, scalability of developed solutions and public support programmes fostering innovation. Obstacles include the difficulty of attracting funds both for company set up and early financier divestment, high admin ...
... solutions and companies looking to implement AI. Drivers include a highly educated workforce, scalability of developed solutions and public support programmes fostering innovation. Obstacles include the difficulty of attracting funds both for company set up and early financier divestment, high admin ...
Soft TDCT: A Fuzzy Approach towards Triangle Density based
... Patterns and useful trends in large datasets has attracted considerable interest recently, and one of the most widely studied problems in this area is the identification and formation of clusters, or densely populated regions in a dataset. Prior work does not adequately address the problem of large ...
... Patterns and useful trends in large datasets has attracted considerable interest recently, and one of the most widely studied problems in this area is the identification and formation of clusters, or densely populated regions in a dataset. Prior work does not adequately address the problem of large ...
Graph-Based Relational Learning: Current and Future Directions
... that captures the variability of the extensions, and is included in the pool of production rules competing based on their ability to compress the input graph. With a proper encoding of this disjunction information, the MDL criterion will tradeoff the complexity of the rule with the amount of compres ...
... that captures the variability of the extensions, and is included in the pool of production rules competing based on their ability to compress the input graph. With a proper encoding of this disjunction information, the MDL criterion will tradeoff the complexity of the rule with the amount of compres ...
CIMTEL- Mining Algorithm for Big Data in Telecommunication
... is called closed if it does not have any superset with the same support. A frequent itemset is said to be maximal if it has no supersets that are frequent. The collection of maximal frequent itemsets is a subset of the collection of closed frequent itemsets, which is a subset of the collection of al ...
... is called closed if it does not have any superset with the same support. A frequent itemset is said to be maximal if it has no supersets that are frequent. The collection of maximal frequent itemsets is a subset of the collection of closed frequent itemsets, which is a subset of the collection of al ...
XGBoost: A Scalable Tree Boosting System
... There are two variants of the algorithm, depending on when the proposal is given. The global variant proposes all the candidate splits during the initial phase of tree construction, and uses the same proposals for split finding at all levels. The local variant re-proposes after each split. The globa ...
... There are two variants of the algorithm, depending on when the proposal is given. The global variant proposes all the candidate splits during the initial phase of tree construction, and uses the same proposals for split finding at all levels. The local variant re-proposes after each split. The globa ...
Natural Language Model Re-usability for Scaling to Different Domains
... In this study, we propose a new approach that reduces the cost of scaling natural language understanding to a large number of domains and experiences without significantly sacrificing the accuracy. The approach consists of a universal slot tagging method and a runtime technique called constrained de ...
... In this study, we propose a new approach that reduces the cost of scaling natural language understanding to a large number of domains and experiences without significantly sacrificing the accuracy. The approach consists of a universal slot tagging method and a runtime technique called constrained de ...
A New Measure for the Accuracy of a Bayesian Network
... The range of values for the degree of accuracy of a Bayesian network, with respect to any data set, is (-∞,0]. Since the MDL formalism evaluates the likelihood of a Bayesian network given a particular data set, the specific range of values for the degree of accuracy of a Bayesian network, with respe ...
... The range of values for the degree of accuracy of a Bayesian network, with respect to any data set, is (-∞,0]. Since the MDL formalism evaluates the likelihood of a Bayesian network given a particular data set, the specific range of values for the degree of accuracy of a Bayesian network, with respe ...
Full Paper (PDF 376832 bytes). - Vanderbilt University School of
... Table 1 lists the three schemes that have been used to generate the 2Ii value. All of them rely on a user defined parameter, n, the ªexpected number of distinct intervals of property attribute Ai .º Since the choice of the 2I value is likely to have a very significant effect on the performance of th ...
... Table 1 lists the three schemes that have been used to generate the 2Ii value. All of them rely on a user defined parameter, n, the ªexpected number of distinct intervals of property attribute Ai .º Since the choice of the 2I value is likely to have a very significant effect on the performance of th ...
CV - School of Computing - University of South Alabama
... Studies, at the UL Lafayette ArTech Fusion, Lafayette, Louisiana, USA. (March 14, 2014). In the spirit of the legend of Ernest Hemingway’s 6 word short story, this project places terse and poignant narratives of land use and loss, restoration and adaptation, attachment to community, resilience, and ...
... Studies, at the UL Lafayette ArTech Fusion, Lafayette, Louisiana, USA. (March 14, 2014). In the spirit of the legend of Ernest Hemingway’s 6 word short story, this project places terse and poignant narratives of land use and loss, restoration and adaptation, attachment to community, resilience, and ...
Flow-metabolism coupling in human visual, motor, and
... BOLD and CBF for all three stimulus levels from the ROI for each individual in the PVC (Fig. 4a), PMC (Fig. 4b), and SMA (Fig. 4c). Measurements from the three different stimulation levels for a given subject are joined by lines, and data points are consistently labeled so that somatosensory activat ...
... BOLD and CBF for all three stimulus levels from the ROI for each individual in the PVC (Fig. 4a), PMC (Fig. 4b), and SMA (Fig. 4c). Measurements from the three different stimulation levels for a given subject are joined by lines, and data points are consistently labeled so that somatosensory activat ...
An Efficient Explanation of Individual Classifications
... often noisy, inconsistent, and incomplete, so various preprocessing methods are used before the appropriate machine learning algorithm is applied. The knowledge we extract this way might not be suitable for immediate use and one or more data postprocessing methods could be applied as well. Data post ...
... often noisy, inconsistent, and incomplete, so various preprocessing methods are used before the appropriate machine learning algorithm is applied. The knowledge we extract this way might not be suitable for immediate use and one or more data postprocessing methods could be applied as well. Data post ...
Tracking evolving communities in large linked networks
... A prominent alternative is to use cocitation analysis (13). In cocitation, two papers are judged similar if they are both cited by another paper. This is a very useful similarity measure. However, for this measure to work properly, a certain time-lag is required in order for papers to build up a cit ...
... A prominent alternative is to use cocitation analysis (13). In cocitation, two papers are judged similar if they are both cited by another paper. This is a very useful similarity measure. However, for this measure to work properly, a certain time-lag is required in order for papers to build up a cit ...
Location-based Activity Recognition
... location is significant and should be assigned a label, from that of labeling places and activities. The first problem was handled by simply assuming that a location is significant if and only if the user spends at least N minutes there, for some fixed threshold N [1, 6, 8, 3]. Some way of restricti ...
... location is significant and should be assigned a label, from that of labeling places and activities. The first problem was handled by simply assuming that a location is significant if and only if the user spends at least N minutes there, for some fixed threshold N [1, 6, 8, 3]. Some way of restricti ...
Artificial Life
... believed by some to be impossible. This is another one of the possibilities. Because of the connections of artificial life to that of science fiction, one could assume a positive response from the Internet marketplace. The following is a basic outline for creating the Internet Entity. Unlike Plan 1, ...
... believed by some to be impossible. This is another one of the possibilities. Because of the connections of artificial life to that of science fiction, one could assume a positive response from the Internet marketplace. The following is a basic outline for creating the Internet Entity. Unlike Plan 1, ...
Medical Diagnosis with C4.5 Rule Preceded by Artificial
... induction are usually regarded as comprehensible techniques because the learned knowledge is expressed in forms such as production rules that are easy to be understood by the user. Rule induction has already been widely applied in medical diagnosis [5], [8], [22]. On the other hand, most connectioni ...
... induction are usually regarded as comprehensible techniques because the learned knowledge is expressed in forms such as production rules that are easy to be understood by the user. Rule induction has already been widely applied in medical diagnosis [5], [8], [22]. On the other hand, most connectioni ...